Stop renting heroes.
Own the knowing.
Every services company forgets what its people know, the day they leave. Supernova is the Company Brain: your data in, an expert ontology on top, and seventeen working agents, a sales squad and a delivery squad, turning model power into outcomes you can actually promise. Priced like bread, not oven-hours.
- WORKING AGENTS
- 17
- RATCHET STAGES
- 9
- UNCHECKED GATES
- 0
Antino, the AI-native services & product company. Built on the Company Brain.
- Use-case tree drafted · 42 itemsSpec Writer · every requirement quotes its sourcepending · Tech Lead
- Ontology derivedData Modeler · entities · states · relationsapproved · Tech Lead
- Mocks built · 6 pagesMock Builder · wearing the approved tokensapproved · Designer
- Session on the ledgermodel calls · tool calls · costopen the run
11:47 PM · A TUESDAY
The project’s memory just resigned.
Meera, a delivery head, is still at her desk when the email lands. One line in the subject: “Resignation.” It’s from the one developer who knows how the payments module actually works.
Not the code, the code is in the repo. The understanding, why it’s built this way, what breaks if you touch it, what the client really meant, walks out in a person’s head, thirty days from now.
Every services company is one resignation away from forgetting how its own software works.
Hi Meera, it’s been a great four years. My last day will be in thirty days. Happy to document what I can before I go.
The payments module’s why, its history, its edge cases, leaves with the sender.
Everything was working. Which is exactly when the dangerous question got asked: why won’t it scale beyond a handful of people?
The 10× lottery
Same tools, same week, one dev gained 10%, another 300%. AI adoption behaved like a lottery ticket, not infrastructure.
You can't promise outcomes on a 30× spread between your own people.
Velocity without visibility
Output exploded, and nobody knew what was actually being built. Things looked great. Solid? Nobody could say.
Speed you can't inspect is risk, not progress.
Heroes don't scale
Quality and quantity depended on who showed up. Every resignation a small fire, every vacation a slowdown, every hire a gamble.
It wasn't a system, it was a collection of heroes.
The handover snaps
No global knowledge base. Move a project from one team to another and it broke, the context left with the person.
The root cause hiding under the other three.
Four fault lines, one root cause: the knowing lived in people, not in the company.
Model power is scattered sticks. The harness is the rope.
On its own an LLM is loose firewood, hallucination, variance, luck. Tie that raw power to org-owned context and gathered knowledge, and the same sticks become something a business can pick up and carry.
Raw power, nothing tying it down.
Bound to the org, firewood you can carry.
Because delivery is a chain of translationsbetween unit artifacts. Every workflow step is one linguistic hop, and “language” can be English, an entity model, a page spec, or a Playwright test.
- 01Use caseENGLISH
“A returning buyer reorders in one tap.”
- 02OntologyENTITIES · STATES
Order, Cart, Reorder: entities, state machines, relations.
- 03Page + mockSCREENS · ROLES
Order history page, one-tap reorder CTA, rendered as a mock.
- 04E2E testPLAYWRIGHT · PASS/FAIL
One spec per use case; the test asserts the cart matches.
ONE PIPELINE, each hop is a translation you can inspect, ground, and repeat
THE COMPANY BRAIN · C.B.
One blueprint that turns raw model power into functions that run.
Not a chatbot bolted to your data, an org-owned brain. Four pieces on one backbone, resolving into outcomes you can measure and promise.
- INGEST
Any data in
Proposals, signed agreements, email threads, recorded calls, the CRM, the whole company, ingested. Nothing about how you work is out of scope.
- STRUCTURE
Expert ontology
An expert-defined structure on that data, the concepts, entities and relationships of your business, made explicit.
- DECOMPOSE
Atomic theory
Every job breaks into atoms, the same structure across every role. An SDR finding prospects, a dev turning a use case into tests: same theory, applied.
- EXECUTE
Harnessed agents
Agents are workers with tools and a ledger: they read the real corpus, save structured artifacts with verbatim provenance quotes, and every run is a session you can open.
THE OUTPUT
Measured outcomes. Model power, turned into functions that run, and results you can promise.
Any data in. Expert ontology on top. Atomic theory applied. Outcomes you can promise.
One deal. Nine ratchet stages. A named human at every gate.
A closed deal births the project, corpus attached: the proposal, the signed agreement, the real threads. From there the journey ratchets, each stage an agent-drafted artifact behind a human gate, and every approved artifact becomes context for the next. The agent proposes; the artifact is the review surface; a person approves.
- 1
Research
GATE · Tech LeadAgents read the project's own corpus: the proposal, the signed agreement, the real email threads. Every claim carries a verbatim quote from its source.
PersonasPersona ResearcherPain pointsevidenced vs researchedCorpus sufficiency checknamed documents - 2
Use cases
GATE · Tech LeadThe product's working spec as a tree: flows, business rules, blocking questions, and a refine loop that regenerates stories and tests together.
Use-case treeSpec WriterUser stories + ACsversionedProvenance quotesverbatim - 3
Ontology
GATE · Tech LeadThe data model derived from the approved use cases: entities, fields, state machines, relationships, rendered as an ERD.
Data model + ERDData ModelerState machinesgated by business rules - 4
Roles
GATE · Tech LeadWhat the product grants, as plain-language permissions naming ontology entities, with personas mapped onto each role.
Role matrixRole Definer - 5
Design
GATE · DesignerThe client product's design language, codified and previewed on a full component kit before anything wears it.
Design language + tokensDesigner agentPreview wallreal components - 6
Pages
GATE · Tech LeadThe surface map: every page owned by a role, with purpose, primary actions, entities shown, and the stories it serves.
Page atlasPage Architect - 7
Mocks
GATE · DesignerOne rendered mock per page, wearing the approved tokens, reviewed in real device widths.
Clickable mocksMock Builder - 8
E2E tests
GATE · Tech LeadOne Playwright spec per use case; the test ids inside are the implementation contract, shipped into the scaffold.
Playwright specsE2E Writer - 9
Planning
GATE · Tech LeadA Jira-shaped plan: milestones, releases with exit-criteria gates, sprints over the backlog, and the change footprint checked before anything mutates.
Plan + boardmilestones · releases · sprintsTech stack proposalTech Stack AdvisorBlast-radius checkImpact Analyst
Stories move through five states on a live board, bugs are first-class issues, QA verify gates sit before done, and release exit criteria only turn green when earned. Eight human roles run it, Designer, Dev and QA included. Every approval is audited, and every agent run is a session you can open: model calls, tool calls, cost.
DATA IS GOLD
Eight years of gold. A Rosetta Stone no one else has.
Every project quietly left a pair behind: what was asked sitting right next to what shipped. Not notes about the work. The work itself, both halves, still attached.
WHAT WAS ASKED
the brief- Specs, scopes & user stories
- Use cases & flows
- What the client actually meant
WHAT SHIPPED
the work- Production code & tests
- Delivered, running systems
- Symbols, files, calls, deps
THE FORGE
Distilled into
the Brain
240
projects
8
years
Every pair poured through, distilled
AGENTS
Workers that actually work
Seventeen of them, grounded in the pairs: they read the real corpus, quote it back verbatim, and go down to the most atomic level of the work, what we came to call infinite control.
240 PROJECTS · 8 YEARS · EVERY PAIR INTACT
This is the moat nobody else has.
Not a demo. A shipped system, working the deal desk and the delivery floor. Open any run and check.
Sales came first: seven agents on the deal desk. Then the honest flinch, would the same harness carry delivery? Ten more agents later, it runs the whole journey, deal to release.
Two squads
IN PRODUCTIONagents
SALES · 7
DELIVERY · 10
The ledger
EVERY RUNThese are not black boxes. Every agent run is a session you can open and read end to end:
- Model callsevery prompt and completion, in order
- Tool callswhat the agent read, and what it saved
- Costthe run, priced, down to the token
- The artifactwith verbatim quotes from its sources
Two unrelated domains. One law: the harness wins.
11:47 PM · THE SAME TUESDAY · ONE YEAR LATER
The resignation email arrives again. Meera reads it, wishes the developer well, and feels nothing break. The payments module’s why, its history, its patterns already live in the Company Brain. Tomorrow, someone picks it up mid-sentence.
The company remembers now.
People add to it. Nobody leaves with it.
Renting heroes by the oven-hour.
You pay for time on a clock. When the person leaves, the knowing leaves with them, and the next project starts from zero.
Priced like bread, not oven-hours.
You buy the outcome, and the knowing stays. Every project feeds the Company Brain, so the next person starts mid-sentence.
Stop renting heroes. Own the knowing.
Antino, the AI-native services & product company. Built on the Company Brain.
Questions, answered.
One org-owned blueprint, a named human at every gate, and a tamper-evident trail behind each decision. The details, without the hand-waving.
No. Every function decomposes into atomic tasks, and the same harness applies to any role. Sales was the first squad, seven agents on the deal desk; delivery was the second, ten agents running the journey from deal to release. The blueprint is the constant, the domain is not.
Your data in, an expert-defined ontology on top, atomic decomposition of the work, and harnessed agents on top of that: workers with tools and a ledger, grounded in your own corpus. It is one org-owned blueprint that turns raw model power into repeatable outcomes.
Every stage is a maker-checker gate: the agent proposes, the structured artifact is the review surface, and a named human approves. Nothing ships unapproved, and every run is a session you can open: model calls, tool calls, cost.
No. The ontology and the agents are org-owned. Your pairs are your moat, not anyone else's, and never folded into a shared model.
Every approval writes a detailed audit event, and every agent run keeps its full session: the model calls, the tool calls, the cost, the artifact it produced. The record is built as the work happens, not reconstructed after.
The first milestone is an approved use-case tree: a reviewed working spec where every requirement quotes the source that earned it. Value shows up as an approved artifact, not a promise.