+
+
+
+
The AI employee a person stands behind.
+
Every company wants AI agents. Almost none can operationalise them — because nobody owns the output. Donna sells the missing layer: agent-speed work with a named human's signature on every outcome, built by a 15-year executive assistant and operated by a Canadian carrier. The wedge is an EA seat. The endgame is the trust layer for the agentic workforce.
+
PREPARED FOR FIBERNETICS / NEWT LEADERSHIP · SEPTEMBER 2026 · CONFIDENTIAL · MARKET & FINANCIAL FIGURES ARE ILLUSTRATIVE PLANNING ASSUMPTIONS
+
+
+
+ 01 · Executive summary
+ Supervision is the product.
+ Gartner forecasts that 40% of agentic-AI projects will be scrapped by 2027 — not because models fail, but because organisations can't govern them. Meanwhile a senior executive assistant costs $120–162K CAD loaded and there aren't enough of them. Donna closes both gaps at once: an AI agent that drafts at machine speed, inside an operating model where a trained person reads everything before it ships under a customer's name.
+ We are not building a better model. We are productising the thing Fibernetics has actually done for fifteen years: run business-critical operations that other companies bet their day on, with a person accountable when it matters. Two engines drive the business:
+
+ - The Desk (revenue now): supervised executive seats at $1,500 CAD/month — Donna drafts, a NEWT-staffed reviewer signs, the customer approves only where they set the line. Live in beta today with a published price and a 5-seat capacity cap.
+ - The Platform (scale): the reviewer dashboard itself, sold as software to the world's ~2M executive assistants — each EA becomes the accountable human for their own fleet of agents and carries 3× the executives. Free for EAs during beta; converts to a SaaS seat.
+
+ The billion-dollar shape (illustrative): ~$100M ARR at a software multiple — roughly 4,000 supervised seats plus 25,000 EA platform seats — reached by expanding from the EA agent into a roster (Finance, Support, Voice) on the same supervised-desk substrate, distributed through Fibernetics' existing carrier and VAR channels.
+
+
+
$1,500
CAD / seat / mo · published
+
+
$100M
ARR target · illustrative
+
+
+
+
+ 02 · Company & product overview
+ NEWT's first AI employee.
+ Mission: make agentic AI usable by real businesses by attaching a named, accountable human to every outcome.
+ What it is: Donna is an AI executive assistant personified on Dawn Gamble — a real senior EA of fifteen years at Fibernetics — and operated under her review. She runs calendars, inboxes, travel, meeting prep and follow-ups. Nothing she produces reaches another human until a person has read it. Donna ships under NEWT, the business division of Fibernetics, a Canadian carrier running business voice and network since 2011.
+ Stage: live early beta. Two marketing sites are deployed with a working application pipeline; pricing is published; the first five supervised seats are open; the reviewer dashboard is spec'd from the operating desk Dawn already runs.
+
+
Origin
Born from a working desk
The blueprint is Abby — the agent Zoe built that automates a real controller's finance reporting, document pipelines and website upkeep, cutting hours of manual work to minutes. Donna generalises that pattern to the executive desk.
+
Positioning
AI-enhanced human
Clients trust a person, not a model. The visible face is a trusted EA; the AI turbocharges her output. Marketing never says "replace your EA" — it says one assistant now covers three desks.
+
Parent
Carrier, not startup
Phone systems, business internet and virtual receptionists already run on Fibernetics infrastructure daily. Donna inherits the operating discipline, the brand and the customer base.
+
+
+
+
+ 03 · Problem & solution
+ An assistant they can't hire. An agent they can't trust.
+
+
The problem
Both options fail
Leaders lose ~18 hrs/week to admin. A senior EA costs $10–13.5K CAD/month loaded and takes months to find. Raw AI agents are instant and cheap — and one confidently wrong email under an executive's name ends the pilot. 40% of agentic projects will die on exactly this (Gartner).
+
The solution
Draft → review → release
Donna drafts at agent speed. A named person at the NEWT desk reads everything outbound within 30 business-minutes. The customer approves only money, commitments and their own name. Every action is logged, attributable, reversible. Silence is a no.
+
The insight competitors keep missing: supervision is not overhead to eliminate — it's the feature customers are actually buying. The EA-facing version inverts the same product: the customer's own assistant becomes the reviewer, and Donna makes her the most capable person in the building instead of the most threatened.
+
+
+
+
+ 04 · Product & how it works
+ One agent, one desk, three authority tiers.
+ The customer draws the line once on an onboarding call; it never moves without them.
+
+
Tier 1 · Automatic
Reversible and internal: calendar moves, filing, triage, drafts into the drafts folder. Donna acts; the desk audits after the fact.
+
Tier 2 · Person-checked
Leaves the building but recoverable: external replies, scheduling with outsiders, chasing commitments. A named reviewer reads in full and sends, fixes, or escalates.
+
Tier 3 · Your signature
Money, promises, the customer's name: waits indefinitely for an explicit yes. No timeout, no default-approve.
+
The Desk dashboard — the real product
+ What Dawn uses today becomes what we sell tomorrow: a single pane of glass where one reviewer runs many principals. Per-person buckets (email, calendar, tasks, notes, documents), a review queue ordered by risk tier, an insights page that surfaces patterns (missed sales calls, recurring requests) as proactive suggestions, and one-tap escalation to the principal. Channels meet people where they are: email and calendar natively, iMessage/SMS domestically, WhatsApp for international scale, Teams and call transcription next.
+ Architecture
+
+ - Claude (Anthropic) + Mosaic — frontier reasoning plus instant deploy of servers, sites and apps; the same stack shipped both beta sites and the live application pipeline in days, not months.
+ - Model failover — automatic fallback to a second provider or a local model, because an assistant that goes down with its vendor isn't an assistant.
+ - Data residency — customer content stays in the Fibernetics environment in Canada; scoped to connected mailboxes; not used to train general models; exported and removed on exit.
+ - No new portal for customers — Donna works inside the email, calendar, phone and finance tools the customer already runs. The dashboard is for the reviewer.
+
+ Working today
+
Live: both product sites, the six-question qualification quiz, published pricing, and a verified application pipeline (form → database → notification email, tagged by seat). In design: the Desk dashboard, drawn from the operating desk it digitises. Not yet live (and said so publicly): Finance, Support and Voice agents.
+
+
+
+
+ 05 · Market analysis
+ A labour market priced for scarcity, meeting a software market priced for scale.
+ All figures below are illustrative planning assumptions from published 2026 ranges, stated so they can be checked — not performance guarantees.
+
+
~$150B
NA exec/admin labour spend
+
~2M
EAs & admin assistants, NA
+
$47B
Agentic-AI market by 2030 (est.)
+
40%
Agentic projects scrapped by '27
+
+ - TAM — the work itself: executive/administrative support labour in North America alone runs on the order of $150B/yr (≈2M roles × ~$75K average loaded cost). Donna monetises a slice of that work at a fraction of its labour price.
+ - SAM — supervised seats + EA software: SMB and mid-market executives without an EA (the NEWT customer profile) plus the ~2M EA population as software seats. Illustratively: 500K reachable executive seats × $18K/yr + 2M EA seats × ~$1.2K/yr ≈ a $11–12B serviceable pool.
+ - SOM — the plan's horizon: ~4,000 supervised seats and ~25,000 platform seats ≈ $100M ARR — under 1% of SAM.
+ - Why now: three-quarters of enterprises say they've adopted agentic AI; almost none have anything genuinely live. The distance between the two is supervision — a job that has to be staffed, trained and productised, which is an operations problem before it is a software problem. Carriers do operations.
+
+
+
+
+
+ 06 · Target customers
+ Who buys, who uses, who spreads it.
+
+
Buys first
The exec who can't hire
SMB founders and executives (the Jordan-at-Delta-Air profile): drowning in admin, can't justify or find a $130K EA, burned or scared by raw AI. Buys the supervised seat.
+
Uses & champions
The overloaded EA
Supports more principals than the role was scoped for. Gets Donna free in beta, becomes the reviewer, covers 3+ execs — and becomes the product's evangelist instead of its victim. Converts to a paid software seat.
+
Distributes
Channel partners
VARs already selling NEWT phone systems experience Donna internally, then resell her to their book. International reach follows WhatsApp, where numbers don't gate by country.
+
+
+
+
+ 07 · Competitive analysis
+ Everyone else sells the model. We sell the signature.
+
+ | Human review built in | Named accountable person | Runs in your tools | Price shape | Weakness Donna exploits |
|---|
+ | Donna (NEWT) | Yes — core design | Yes, you meet her | Yes | $1,500 CAD/seat/mo · EA seat SaaS | — |
+ | Autonomous AI EAs (Lindy, Martin, Ohai) | No — autonomous by design | No | Partial | $30–500/mo | One wrong email under your name ends the pilot; no one owns the output |
+ | AI email tools (Fyxer, Superhuman AI) | You are the reviewer | No | Yes | $30–90/mo | Moves the reading to your evening instead of removing it |
+ | Suite copilots (Microsoft Copilot, Gemini) | You are the reviewer | No | Native | $20–40/user/mo | Generic; no service, no accountability, no desk |
+ | Human VA services (Belay, Time etc, Athena) | Human does the work | Rota / offshore | Yes | $1,600–3,400+/mo part-time | Human speed at human cost; one set of hands; vacations |
+ | Hiring a senior EA | N/A | Yes | Yes | $10–13.5K/mo loaded | Can't hire them fast enough; single point of failure |
+
The moat, honestly
+
+ - The reviewer network + correction loop. Corrections don't go into a ticket queue — the reviewer is the designer, so a correction changes the product that week. Every supervised seat compounds a proprietary dataset of "what good judgment looks like" that model vendors don't have.
+ - The EA flywheel. Every other vendor threatens EAs; we arm them. The free assistant seat recruits the exact population that (a) buys software seats, (b) staffs our desk as we scale, and (c) sits between every vendor and every executive inbox as gatekeeper.
+ - Carrier trust + channel. Fifteen years of business-critical uptime, data in Canada, one accountable throat — plus an installed base and VAR network no agent startup can rent.
+ - Switching cost. Connected mailboxes, calendars, tone models and authority tables make seat N+1 cheaper for us and leaving costlier for them.
+
+
+
+
+
+ 08 · Go-to-market
+ Concentric circles, each one funding the next.
+
+ - Circle 0 — the 5-seat beta (now). Local, friendly businesses within ~100 km for in-person support; warm leads first. Free during beta, published $1,500 price, capacity cap stated plainly. The intake pipeline is live and tags applicants by seat.
+ - Circle 1 — VARs as customers (Q1'27). Resellers of NEWT phone systems get seats before they sell them — the demo is their own desk. Their book of SMBs becomes the first paid cohort.
+ - Circle 2 — the EA community (rolling). donna-for-eas is the acquisition engine: free assistant seats, a written "pitch your exec" note in the product, and the only vendor message in the category that EAs can forward without fearing for their job. EAs pull Donna into companies; execs don't have to be sold.
+ - Circle 3 — carrier bundle + international. Donna joins the NEWT bundle (voice + internet + receptionist + AI employee, one bill, one throat). WhatsApp unlocks non-NA markets where iMessage/SMS numbers fragment.
+
+ Message discipline
+
To executives: "hire your first AI employee — a real person signs her work." To EAs: "you already are the assistant; this is how you cover three of them." Never "replace your EA." The honesty register — published pricing, stated limits, no SOC 2 yet, seats genuinely capped — is itself the differentiator in a category drowning in overclaim.
+
+
+
+
+ 09 · Business model
+ Two engines, one substrate.
+
+ | Stream | Price (CAD) | Reviewer | Illustrative gross margin | Role in the plan |
|---|
+ | Supervised executive seat | $1,500 / mo | NEWT desk | ~50–60% at 8–10 seats/reviewer | Revenue now, trust proof, correction data |
+ | EA platform seat | Free in beta → ~$99–299 / mo | The customer's EA | ~85% | Scale engine; no desk to staff behind it |
+ | Agent roster add-ons (FIN / SUP / VOX) | Per-agent seat pricing | Mixed | Blended | Expansion revenue on the same substrate |
+ | Carrier bundle uplift | Bundled MRR | — | — | Retention + distribution, defends core NEWT base |
+
Unit economics — supervised seat (illustrative)
+
+ revenue / seat = $1,500 / mo
+ reviewer (loaded ~$7.5K/mo) across 8–10 seats ≈ $750–940 / seat
+ AI compute + infra ≈ $75–150 / seat
+ → gross margin ≈ $400–700 / seat / mo (~50–60% at desk maturity)
+ platform seat @ $149: cost to serve ≈ $20 → ≈ 85% margin
+
+ The strategic point: the supervised seat is priced at roughly a seventh of a loaded EA and below a part-time offshore VA — while the platform seat costs less than an EA's monthly parking. Neither engine asks the customer to believe anything about AI; both ask them to believe a person they've met.
+
+
+
+
+ 10 · Operations
+ The desk is the factory.
+
+ - Review SLA: outbound checked in under 30 business-minutes (2 hrs off-hours); when we'll miss it, Donna hands the customer the finished draft to send themselves — the customer is never blocked on us.
+ - Desk scaling: Dawn is reviewer #1 and the training standard. Each new reviewer is an experienced EA, trained on the authority-tier playbook, shadowing live seats before holding their own. Target ratio: 8–10 supervised seats per reviewer at maturity; customers are told by name when anyone new touches their account.
+ - Onboarding: Day 0 thirty-minute call and authority table; days 1–3 shadow mode (Donna reads, touches nothing); days 4–10 Tier 1 live; days 11–30 the customer moves the line.
+ - Reliability: operated on carrier discipline — monitored, multi-model failover, incident paths that already exist for voice and network customers.
+ - Security roadmap: data-processing terms before anything connects; scoped mailbox access, revoked on disconnect; SOC 2 Type I in the funded plan. Until certified, we say so plainly — the honesty is load-bearing.
+
+
+
+
+
+ 11 · Team
+ The person, the builder, the carrier.
+
+
Product · Operations
Dawn Gamble
Senior Executive Assistant, Fibernetics — fifteen years running the founders' desk. Designed Donna from her own job, reviews every beta seat, and trains the desk as it grows. The face customers meet on day zero.
+
Engineering · AI
Zoe Cross
Built and shipped the stack: the agent architecture (proven on Abby's finance desk), both product sites, and the live application pipeline. Owns the Claude + Mosaic platform, failover design and the Desk dashboard build.
+
Parent · Channel
Fibernetics / NEWT
Canadian carrier since 2011: infrastructure, uptime discipline, installed SMB base, VAR network, brand, and the founders' direct sponsorship of the project.
+
+
+
+
+ 12 · Financial plan
+ From five seats to $100M ARR — the arithmetic, not the poetry.
+ Every figure is an illustrative planning assumption for decision-making, not a forecast.
+
+ | Phase (illustrative) | Supervised seats | Platform seats | ARR (CAD) | Desk staff | Stance |
|---|
+ | Beta → mo 6 | 5 → 25 | 50 free | $0 → $450K | Dawn + 2 | Investment |
+ | Year 1 | 100 | 500 @ $149 | ≈ $2.7M | ~12 | Near break-even |
+ | Year 2 | 400 | 3,000 | ≈ $12.5M | ~45 | Profitable desk |
+ | Year 3–4 | 1,500 | 10,000 | ≈ $45M | Regional desks | Roster live (FIN/SUP/VOX) |
+ | Year 5 target | 4,000 | 25,000+ | ≈ $100M | Franchise-model desks | ≈ $1B at ~10× ARR |
+
+ - Cost structure: reviewers (the dominant variable cost, ~50% of supervised-seat revenue at maturity), AI compute (~5–10%), platform engineering (fixed, small — the stack is deliberately lean), sales via existing channel (low CAC by design).
+ - Break-even (illustrative): ~35–40 supervised seats carries the early team; the platform seat's 85% margin pulls blended margin up as mix shifts toward software — which is the whole strategic design.
+ - Funding need: $1.5M CAD for 18 months (internal venture allocation or seed): Desk dashboard build, 6 reviewers hired and trained, SOC 2 Type I, WhatsApp + voice channels, VAR partner program, and marketing that stays in the honesty register.
+ - Use of funds: ~45% engineering, ~30% desk staffing & training, ~15% compliance/security, ~10% GTM.
+
+
+
+
+
+ 13 · Roadmap
+ Three horizons.
+
+
Horizon 1 · now → 6 mo
Prove the desk
Fill 5 beta seats from live intake. Ship the Desk dashboard MVP (buckets, review queue, insights). Convert beta → paid with an explicit yes. Hire reviewers 2–3. SOC 2 program start. VAR pilot with 2 resellers.
+
Horizon 2 · 6–18 mo
Scale the two engines
EA platform seat GA with self-serve pricing. FIN agent live (invoice chasing, expense coding — reviewed before anything posts). WhatsApp channel for international. 100+ supervised seats, 500+ platform seats.
+
Horizon 3 · 18 mo +
Own the category
VOX voice agent on NEWT's own telephony. Donna-certified reviewer program → a marketplace where any certified EA sells supervised capacity on our rails, and we take the platform cut. The trust layer for agentic work.
+
+
+
+
+ 14 · Risks & mitigations
+ What kills this, and what we've done about each.
+
+
Reviewer scaling is the bottleneckBy design: the platform seat needs no desk (customer's EA reviews), the certification program turns the labour constraint into a marketplace, and seats-per-reviewer rises as Tier 1 automation earns trust.
+
Key-person risk: DawnThe authority-tier playbook and training program exist precisely to encode her judgment; reviewer #2–3 are hired in Horizon 1; the correction loop writes her standards into the product weekly.
+
Suite copilots commoditise draftingLet them — drafting was never the product. Copilots make our COGS cheaper and still leave the customer as their own reviewer at 11 p.m. Accountability plus service doesn't ship in a suite SKU.
+
Services margin drags the multipleMix-shift is the plan: supervised seats are the wedge and the data engine; platform seats at ~85% margin become the majority of ARR by Year 3 (illustrative).
+
No security certification yetStated plainly on the public site today; DPA before anything connects; scoped access, revoked on disconnect; SOC 2 Type I funded in the ask. Honesty now beats implication later.
+
Model/vendor dependencyMulti-model failover is in the architecture (Claude primary, second provider or local fallback), and the review layer means a weaker model degrades speed, not safety.
+
A public error under a customer's nameTier design makes it structurally hard (Tier 3 waits indefinitely); full action logs make any incident auditable; the correction becomes a product change the same week — and we say so.
+
Beta converts poorly at $1,500Price is published now specifically so conversion is tested honestly from day one; fallback positioning against $1,600–3,400 part-time VAs holds margin; platform seat catches the price-sensitive.
+
+
+
+
+ 15 · The ask & next steps
+ Green-light the venture. The beta is already live.
+
+ - Decision: constitute Donna as a NEWT product line with $1.5M CAD / 18-month allocation and Dawn formally allocated to it.
+ - Next 30 days: fill the 5 beta seats from live intake (first target: the warm Delta Air lead); start the Desk dashboard build; begin reviewer #2 recruitment from the EA community funnel; kick off SOC 2 scoping.
+ - Success gate for the next tranche: 5 seats live with retention through day 30, review SLA held, and a signed VAR pilot — evidence, not projections.
+
+ The one-sentence case
+
Everyone is racing to make agents more autonomous; the customers with money are begging for someone to make them accountable — and accountability is the only part of this Fibernetics has already been selling for fifteen years.
+
Market sizes, financial projections, margins and seat counts in this document are illustrative planning assumptions drawn from published 2026 ranges and internal estimates; they are not forecasts or performance guarantees. Product claims describe the live beta as deployed. Prepared with the founders' knowledge for internal decision-making.
+
+
+
+
+
+
+
+
+
The AI employee a person stands behind.
+
Every company wants AI agents. Almost none can operationalise them — because nobody owns the output. Donna sells the missing layer: agent-speed work with a named human's signature on every outcome, built by a 15-year executive assistant and operated by a Canadian carrier. The wedge is an EA seat. The endgame is the trust layer for the agentic workforce.
+
PREPARED FOR FIBERNETICS / NEWT LEADERSHIP · SEPTEMBER 2026 · CONFIDENTIAL · MARKET & FINANCIAL FIGURES ARE ILLUSTRATIVE PLANNING ASSUMPTIONS
+
+
+
+ 01 · Executive summary
+ Supervision is the product.
+ Gartner forecasts that 40% of agentic-AI projects will be scrapped by 2027 — not because models fail, but because organisations can't govern them. Meanwhile a senior executive assistant costs $120–162K CAD loaded and there aren't enough of them. Donna closes both gaps at once: an AI agent that drafts at machine speed, inside an operating model where a trained person reads everything before it ships under a customer's name.
+ We are not building a better model. We are productising the thing Fibernetics has actually done for fifteen years: run business-critical operations that other companies bet their day on, with a person accountable when it matters. Two engines drive the business:
+
+ - The Desk (revenue now): supervised executive seats at $1,500 CAD/month — Donna drafts, a NEWT-staffed reviewer signs, the customer approves only where they set the line. Live in beta today with a published price and a 5-seat capacity cap.
+ - The Platform (scale): the reviewer dashboard itself, sold as software to the world's ~2M executive assistants — each EA becomes the accountable human for their own fleet of agents and carries 3× the executives. Free for EAs during beta; converts to a SaaS seat.
+
+ The billion-dollar shape (illustrative): ~$100M ARR at a software multiple — roughly 4,000 supervised seats plus 25,000 EA platform seats — reached by expanding from the EA agent into a roster (Finance, Support, Voice) on the same supervised-desk substrate, distributed through Fibernetics' existing carrier and VAR channels.
+
+
+
$1,500
CAD / seat / mo · published
+
+
$100M
ARR target · illustrative
+
+
+
+
+ 02 · Company & product overview
+ NEWT's first AI employee.
+ Mission: make agentic AI usable by real businesses by attaching a named, accountable human to every outcome.
+ What it is: Donna is an AI executive assistant personified on Dawn Gamble — a real senior EA of fifteen years at Fibernetics — and operated under her review. She runs calendars, inboxes, travel, meeting prep and follow-ups. Nothing she produces reaches another human until a person has read it. Donna ships under NEWT, the business division of Fibernetics, a Canadian carrier running business voice and network since 2011.
+ Stage: live early beta. Two marketing sites are deployed with a working application pipeline; pricing is published; the first five supervised seats are open; the reviewer dashboard is spec'd from the operating desk Dawn already runs.
+
+
Origin
Born from a working desk
The blueprint is Abby — the agent Zoe built that automates a real controller's finance reporting, document pipelines and website upkeep, cutting hours of manual work to minutes. Donna generalises that pattern to the executive desk.
+
Positioning
AI-enhanced human
Clients trust a person, not a model. The visible face is a trusted EA; the AI turbocharges her output. Marketing never says "replace your EA" — it says one assistant now covers three desks.
+
Parent
Carrier, not startup
Phone systems, business internet and virtual receptionists already run on Fibernetics infrastructure daily. Donna inherits the operating discipline, the brand and the customer base.
+
+
+
+
+ 03 · Problem & solution
+ An assistant they can't hire. An agent they can't trust.
+
+
The problem
Both options fail
Leaders lose ~18 hrs/week to admin. A senior EA costs $10–13.5K CAD/month loaded and takes months to find. Raw AI agents are instant and cheap — and one confidently wrong email under an executive's name ends the pilot. 40% of agentic projects will die on exactly this (Gartner).
+
The solution
Draft → review → release
Donna drafts at agent speed. A named person at the NEWT desk reads everything outbound within 30 business-minutes. The customer approves only money, commitments and their own name. Every action is logged, attributable, reversible. Silence is a no.
+
The insight competitors keep missing: supervision is not overhead to eliminate — it's the feature customers are actually buying. The EA-facing version inverts the same product: the customer's own assistant becomes the reviewer, and Donna makes her the most capable person in the building instead of the most threatened.
+
+
+
+
+ 04 · Product & how it works
+ One agent, one desk, three authority tiers.
+ The customer draws the line once on an onboarding call; it never moves without them.
+
+
Tier 1 · Automatic
Reversible and internal: calendar moves, filing, triage, drafts into the drafts folder. Donna acts; the desk audits after the fact.
+
Tier 2 · Person-checked
Leaves the building but recoverable: external replies, scheduling with outsiders, chasing commitments. A named reviewer reads in full and sends, fixes, or escalates.
+
Tier 3 · Your signature
Money, promises, the customer's name: waits indefinitely for an explicit yes. No timeout, no default-approve.
+
The Desk dashboard — the real product
+ What Dawn uses today becomes what we sell tomorrow: a single pane of glass where one reviewer runs many principals. Per-person buckets (email, calendar, tasks, notes, documents), a review queue ordered by risk tier, an insights page that surfaces patterns (missed sales calls, recurring requests) as proactive suggestions, and one-tap escalation to the principal. Channels meet people where they are: email and calendar natively, iMessage/SMS domestically, WhatsApp for international scale, Teams and call transcription next.
+ Architecture
+
+ - Claude (Anthropic) + Mosaic — frontier reasoning plus instant deploy of servers, sites and apps; the same stack shipped both beta sites and the live application pipeline in days, not months.
+ - Model failover — automatic fallback to a second provider or a local model, because an assistant that goes down with its vendor isn't an assistant.
+ - Data residency — customer content stays in the Fibernetics environment in Canada; scoped to connected mailboxes; not used to train general models; exported and removed on exit.
+ - No new portal for customers — Donna works inside the email, calendar, phone and finance tools the customer already runs. The dashboard is for the reviewer.
+
+ Working today
+
Live: both product sites, the six-question qualification quiz, published pricing, and a verified application pipeline (form → database → notification email, tagged by seat). In design: the Desk dashboard, drawn from the operating desk it digitises. Not yet live (and said so publicly): Finance, Support and Voice agents.
+
+
+
+
+ 05 · Market analysis
+ A labour market priced for scarcity, meeting a software market priced for scale.
+ All figures below are illustrative planning assumptions from published 2026 ranges, stated so they can be checked — not performance guarantees.
+
+
~$150B
NA exec/admin labour spend
+
~2M
EAs & admin assistants, NA
+
$47B
Agentic-AI market by 2030 (est.)
+
40%
Agentic projects scrapped by '27
+
+ - TAM — the work itself: executive/administrative support labour in North America alone runs on the order of $150B/yr (≈2M roles × ~$75K average loaded cost). Donna monetises a slice of that work at a fraction of its labour price.
+ - SAM — supervised seats + EA software: SMB and mid-market executives without an EA (the NEWT customer profile) plus the ~2M EA population as software seats. Illustratively: 500K reachable executive seats × $18K/yr + 2M EA seats × ~$1.2K/yr ≈ a $11–12B serviceable pool.
+ - SOM — the plan's horizon: ~4,000 supervised seats and ~25,000 platform seats ≈ $100M ARR — under 1% of SAM.
+ - Why now: three-quarters of enterprises say they've adopted agentic AI; almost none have anything genuinely live. The distance between the two is supervision — a job that has to be staffed, trained and productised, which is an operations problem before it is a software problem. Carriers do operations.
+
+
+
+
+
+ 06 · Target customers
+ Who buys, who uses, who spreads it.
+
+
Buys first
The exec who can't hire
SMB founders and executives (the Jordan-at-Delta-Air profile): drowning in admin, can't justify or find a $130K EA, burned or scared by raw AI. Buys the supervised seat.
+
Uses & champions
The overloaded EA
Supports more principals than the role was scoped for. Gets Donna free in beta, becomes the reviewer, covers 3+ execs — and becomes the product's evangelist instead of its victim. Converts to a paid software seat.
+
Distributes
Channel partners
VARs already selling NEWT phone systems experience Donna internally, then resell her to their book. International reach follows WhatsApp, where numbers don't gate by country.
+
+
+
+
+ 07 · Competitive analysis
+ Everyone else sells the model. We sell the signature.
+
+ | Human review built in | Named accountable person | Runs in your tools | Price shape | Weakness Donna exploits |
|---|
+ | Donna (NEWT) | Yes — core design | Yes, you meet her | Yes | $1,500 CAD/seat/mo · EA seat SaaS | — |
+ | Autonomous AI EAs (Lindy, Martin, Ohai) | No — autonomous by design | No | Partial | $30–500/mo | One wrong email under your name ends the pilot; no one owns the output |
+ | AI email tools (Fyxer, Superhuman AI) | You are the reviewer | No | Yes | $30–90/mo | Moves the reading to your evening instead of removing it |
+ | Suite copilots (Microsoft Copilot, Gemini) | You are the reviewer | No | Native | $20–40/user/mo | Generic; no service, no accountability, no desk |
+ | Human VA services (Belay, Time etc, Athena) | Human does the work | Rota / offshore | Yes | $1,600–3,400+/mo part-time | Human speed at human cost; one set of hands; vacations |
+ | Hiring a senior EA | N/A | Yes | Yes | $10–13.5K/mo loaded | Can't hire them fast enough; single point of failure |
+
The moat, honestly
+
+ - The reviewer network + correction loop. Corrections don't go into a ticket queue — the reviewer is the designer, so a correction changes the product that week. Every supervised seat compounds a proprietary dataset of "what good judgment looks like" that model vendors don't have.
+ - The EA flywheel. Every other vendor threatens EAs; we arm them. The free assistant seat recruits the exact population that (a) buys software seats, (b) staffs our desk as we scale, and (c) sits between every vendor and every executive inbox as gatekeeper.
+ - Carrier trust + channel. Fifteen years of business-critical uptime, data in Canada, one accountable throat — plus an installed base and VAR network no agent startup can rent.
+ - Switching cost. Connected mailboxes, calendars, tone models and authority tables make seat N+1 cheaper for us and leaving costlier for them.
+
+
+
+
+
+ 08 · Go-to-market
+ Concentric circles, each one funding the next.
+
+ - Circle 0 — the 5-seat beta (now). Local, friendly businesses within ~100 km for in-person support; warm leads first. Free during beta, published $1,500 price, capacity cap stated plainly. The intake pipeline is live and tags applicants by seat.
+ - Circle 1 — VARs as customers (Q1'27). Resellers of NEWT phone systems get seats before they sell them — the demo is their own desk. Their book of SMBs becomes the first paid cohort.
+ - Circle 2 — the EA community (rolling). donna-for-eas is the acquisition engine: free assistant seats, a written "pitch your exec" note in the product, and the only vendor message in the category that EAs can forward without fearing for their job. EAs pull Donna into companies; execs don't have to be sold.
+ - Circle 3 — carrier bundle + international. Donna joins the NEWT bundle (voice + internet + receptionist + AI employee, one bill, one throat). WhatsApp unlocks non-NA markets where iMessage/SMS numbers fragment.
+
+ Message discipline
+
To executives: "hire your first AI employee — a real person signs her work." To EAs: "you already are the assistant; this is how you cover three of them." Never "replace your EA." The honesty register — published pricing, stated limits, no SOC 2 yet, seats genuinely capped — is itself the differentiator in a category drowning in overclaim.
+
+
+
+
+ 09 · Business model
+ Two engines, one substrate.
+
+ | Stream | Price (CAD) | Reviewer | Illustrative gross margin | Role in the plan |
|---|
+ | Supervised executive seat | $1,500 / mo | NEWT desk | ~50–60% at 8–10 seats/reviewer | Revenue now, trust proof, correction data |
+ | EA platform seat | Free in beta → ~$99–299 / mo | The customer's EA | ~85% | Scale engine; no desk to staff behind it |
+ | Agent roster add-ons (FIN / SUP / VOX) | Per-agent seat pricing | Mixed | Blended | Expansion revenue on the same substrate |
+ | Carrier bundle uplift | Bundled MRR | — | — | Retention + distribution, defends core NEWT base |
+
Unit economics — supervised seat (illustrative)
+
+ revenue / seat = $1,500 / mo
+ reviewer (loaded ~$7.5K/mo) across 8–10 seats ≈ $750–940 / seat
+ AI compute + infra ≈ $75–150 / seat
+ → gross margin ≈ $400–700 / seat / mo (~50–60% at desk maturity)
+ platform seat @ $149: cost to serve ≈ $20 → ≈ 85% margin
+
+ The strategic point: the supervised seat is priced at roughly a seventh of a loaded EA and below a part-time offshore VA — while the platform seat costs less than an EA's monthly parking. Neither engine asks the customer to believe anything about AI; both ask them to believe a person they've met.
+
+
+
+
+ 10 · Operations
+ The desk is the factory.
+
+ - Review SLA: outbound checked in under 30 business-minutes (2 hrs off-hours); when we'll miss it, Donna hands the customer the finished draft to send themselves — the customer is never blocked on us.
+ - Desk scaling: Dawn is reviewer #1 and the training standard. Each new reviewer is an experienced EA, trained on the authority-tier playbook, shadowing live seats before holding their own. Target ratio: 8–10 supervised seats per reviewer at maturity; customers are told by name when anyone new touches their account.
+ - Onboarding: Day 0 thirty-minute call and authority table; days 1–3 shadow mode (Donna reads, touches nothing); days 4–10 Tier 1 live; days 11–30 the customer moves the line.
+ - Reliability: operated on carrier discipline — monitored, multi-model failover, incident paths that already exist for voice and network customers.
+ - Security roadmap: data-processing terms before anything connects; scoped mailbox access, revoked on disconnect; SOC 2 Type I in the funded plan. Until certified, we say so plainly — the honesty is load-bearing.
+
+
+
+
+
+ 11 · Team
+ The person, the builder, the carrier.
+
+
Product · Operations
Dawn Gamble
Senior Executive Assistant, Fibernetics — fifteen years running the founders' desk. Designed Donna from her own job, reviews every beta seat, and trains the desk as it grows. The face customers meet on day zero.
+
Engineering · AI
Zoe Cross
Built and shipped the stack: the agent architecture (proven on Abby's finance desk), both product sites, and the live application pipeline. Owns the Claude + Mosaic platform, failover design and the Desk dashboard build.
+
Parent · Channel
Fibernetics / NEWT
Canadian carrier since 2011: infrastructure, uptime discipline, installed SMB base, VAR network, brand, and the founders' direct sponsorship of the project.
+
+
+
+
+ 12 · Financial plan
+ From five seats to $100M ARR — the arithmetic, not the poetry.
+ Every figure is an illustrative planning assumption for decision-making, not a forecast.
+
+ | Phase (illustrative) | Supervised seats | Platform seats | ARR (CAD) | Desk staff | Stance |
|---|
+ | Beta → mo 6 | 5 → 25 | 50 free | $0 → $450K | Dawn + 2 | Investment |
+ | Year 1 | 100 | 500 @ $149 | ≈ $2.7M | ~12 | Near break-even |
+ | Year 2 | 400 | 3,000 | ≈ $12.5M | ~45 | Profitable desk |
+ | Year 3–4 | 1,500 | 10,000 | ≈ $45M | Regional desks | Roster live (FIN/SUP/VOX) |
+ | Year 5 target | 4,000 | 25,000+ | ≈ $100M | Franchise-model desks | ≈ $1B at ~10× ARR |
+
+ - Cost structure: reviewers (the dominant variable cost, ~50% of supervised-seat revenue at maturity), AI compute (~5–10%), platform engineering (fixed, small — the stack is deliberately lean), sales via existing channel (low CAC by design).
+ - Break-even (illustrative): ~35–40 supervised seats carries the early team; the platform seat's 85% margin pulls blended margin up as mix shifts toward software — which is the whole strategic design.
+ - Funding need: $1.5M CAD for 18 months (internal venture allocation or seed): Desk dashboard build, 6 reviewers hired and trained, SOC 2 Type I, WhatsApp + voice channels, VAR partner program, and marketing that stays in the honesty register.
+ - Use of funds: ~45% engineering, ~30% desk staffing & training, ~15% compliance/security, ~10% GTM.
+
+
+
+
+
+ 13 · Roadmap
+ Three horizons.
+
+
Horizon 1 · now → 6 mo
Prove the desk
Fill 5 beta seats from live intake. Ship the Desk dashboard MVP (buckets, review queue, insights). Convert beta → paid with an explicit yes. Hire reviewers 2–3. SOC 2 program start. VAR pilot with 2 resellers.
+
Horizon 2 · 6–18 mo
Scale the two engines
EA platform seat GA with self-serve pricing. FIN agent live (invoice chasing, expense coding — reviewed before anything posts). WhatsApp channel for international. 100+ supervised seats, 500+ platform seats.
+
Horizon 3 · 18 mo +
Own the category
VOX voice agent on NEWT's own telephony. Donna-certified reviewer program → a marketplace where any certified EA sells supervised capacity on our rails, and we take the platform cut. The trust layer for agentic work.
+
+
+
+
+ 14 · Risks & mitigations
+ What kills this, and what we've done about each.
+
+
Reviewer scaling is the bottleneckBy design: the platform seat needs no desk (customer's EA reviews), the certification program turns the labour constraint into a marketplace, and seats-per-reviewer rises as Tier 1 automation earns trust.
+
Key-person risk: DawnThe authority-tier playbook and training program exist precisely to encode her judgment; reviewer #2–3 are hired in Horizon 1; the correction loop writes her standards into the product weekly.
+
Suite copilots commoditise draftingLet them — drafting was never the product. Copilots make our COGS cheaper and still leave the customer as their own reviewer at 11 p.m. Accountability plus service doesn't ship in a suite SKU.
+
Services margin drags the multipleMix-shift is the plan: supervised seats are the wedge and the data engine; platform seats at ~85% margin become the majority of ARR by Year 3 (illustrative).
+
No security certification yetStated plainly on the public site today; DPA before anything connects; scoped access, revoked on disconnect; SOC 2 Type I funded in the ask. Honesty now beats implication later.
+
Model/vendor dependencyMulti-model failover is in the architecture (Claude primary, second provider or local fallback), and the review layer means a weaker model degrades speed, not safety.
+
A public error under a customer's nameTier design makes it structurally hard (Tier 3 waits indefinitely); full action logs make any incident auditable; the correction becomes a product change the same week — and we say so.
+
Beta converts poorly at $1,500Price is published now specifically so conversion is tested honestly from day one; fallback positioning against $1,600–3,400 part-time VAs holds margin; platform seat catches the price-sensitive.
+
+
+
+
+ 15 · The ask & next steps
+ Green-light the venture. The beta is already live.
+
+ - Decision: constitute Donna as a NEWT product line with $1.5M CAD / 18-month allocation and Dawn formally allocated to it.
+ - Next 30 days: fill the 5 beta seats from live intake (first target: the warm Delta Air lead); start the Desk dashboard build; begin reviewer #2 recruitment from the EA community funnel; kick off SOC 2 scoping.
+ - Success gate for the next tranche: 5 seats live with retention through day 30, review SLA held, and a signed VAR pilot — evidence, not projections.
+
+ The one-sentence case
+
Everyone is racing to make agents more autonomous; the customers with money are begging for someone to make them accountable — and accountability is the only part of this Fibernetics has already been selling for fifteen years.
+
Market sizes, financial projections, margins and seat counts in this document are illustrative planning assumptions drawn from published 2026 ranges and internal estimates; they are not forecasts or performance guarantees. Product claims describe the live beta as deployed. Prepared with the founders' knowledge for internal decision-making.
+
+
+
+
+
+
+
+
Donna · NEWT by Fibernetics
+
Executive Summary
+
+
+
Beta live · intake open
+
PDF ↓
+
+
+
+
The AI employee a person stands behind.
+
Donna is an AI executive assistant operated under a named human reviewer — designed by a 15-year EA from her own desk, run by a Canadian carrier. She drafts at agent speed; nothing reaches another human until a person has read it. Two engines: supervised executive seats at $1,500 CAD/mo today, and the reviewer platform sold to the world’s ~2M executive assistants tomorrow. The endgame is the trust layer for the agentic workforce.
+
+
+
+
The problem
+
Can’t hire, can’t trust
+
Executives lose ~18 hrs/week to admin. A senior EA runs $10–13.5K CAD/mo loaded and can’t be found; raw AI agents are instant — and 40% of agentic projects will be scrapped by 2027 because nobody owns the output.
+
+
+
The solution
+
Draft → review → release
+
Three authority tiers the customer sets once: routine runs alone, outbound is person-checked in <30 business-minutes, money and commitments wait for an explicit yes. Logged, attributable, reversible. Silence is a no.
+
+
+
Why it wins
+
Supervision is the product
+
Every rival sells the model and leaves you as reviewer at 11 p.m. We sell the signature: a named person, carrier-grade operations, data in Canada — and the only pitch in the category that EAs forward instead of fear.
+
+
+
+
+
+
$1,500
CAD/seat/mo · published
+
~$150B
NA admin labour · illustr.
+
$100M
ARR target · illustr.
+
+
+
+
+
Business model · two engines
+
+ supervised seat = $1,500/mo, reviewer across 8–10 seats → ~55% margin
+ platform seat (their EA reviews) = $99–299/mo · ~85% margin
+ path: 4,000 seats + 25,000 EA seats ≈ $100M ARR
+
+
A seventh of an EA. Less than a VA.
+
Then FIN / SUP / VOX agents on the same desk, sold through NEWT’s carrier & VAR channel. Figures illustrative.
+
+
+
Where we are
+
✓ Two product sites live DONE
+
✓ Application intake → DB → email, verified DONE
+
✓ Pricing published · 5-seat beta open DONE
+
! Desk dashboard MVP build NEXT
+
! SOC 2 Type I · reviewer #2 hire GATE
+
+
+
+
+
The ask
+
Constitute Donna as a NEWT product line: $1.5M CAD over 18 months, Dawn formally allocated. Next 30 days: fill the five beta seats from live intake, start the Desk dashboard, recruit reviewer #2. Gate for the next tranche: five seats retained through day 30 with the review SLA held — evidence, not projections.
+
+
+
+