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 harnessed agents that turn model power into outcomes you can actually promise. Priced like bread, not oven-hours.
- SPEC → CODE
- 85%+
- PROJECTS DISTILLED
- 240
- UNCHECKED GATES
- 0
Antino, the AI-native services & product company. Built on the Company Brain.
- Spec compiled · 42 itemsEARS + Gherkin · traced to the contractpending · PM
- Ontology draftedentities · rules · RBAC · glossaryapproved · Tech Lead
- Code generated · PR #218with tests + AI provenancein review
- Gate evidence sealedSOC 2 · EU AI Act Art. 14tamper-evident
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, a user story, a test case, or Python.
- 01Use caseENGLISH
“A returning buyer reorders in one tap.”
- 02User storySPEC
As a buyer, I can reorder from my history.
- 03Dev planDESIGN
Reorder endpoint + one-tap CTA on the order card.
- 04Code + testsPYTHON · PASS/FAIL
POST /reorder → 201; test asserts 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
Docs, CRM, repos, tickets, threads, 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
Fine-tuned agents, harnessed to the ontology and the atoms, model power turned into functions that actually run.
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 contract. Six engines. A named human at every gate.
The whole services pipeline, encoded, every artifact pinned to the standard it follows, every stage a maker-checker gate. The agent proposes; the artifact is the review surface; a person approves. This is the moat: 240 projects of “what was asked → what shipped,” distilled into templates and an ontology no one else has.
- 0
Intake
GATE · Sales LeadThe Auto-SDR turns a signal into a qualified opportunity.
Opportunity briefMEDDPICCDiscovery notesverbatim + timestampsRFP responseAPMP · NOSE - 1
Sales OS
GATE · Sales Lead · Architect · Legal · ClientThe nine-artifact pre-contract chain, each agent drafts from everything approved before it.
Scope documentPMBOKBRD → PRD → FRDBABOK · IEEE 830UI/UX packagefidelity ladderArchitectureC4 · Well-ArchitectedMSA + SOW+ AI-IP clausesIntegration docsOpenAPI · ICD - 2
Specification
GATE · PM + Solution ArchitectThe spec is the unit of programming, code is its lossy projection.
Spec itemsEARS · ISO 29148Acceptance criteriaGherkin · Spec KitSpec documentSpec Kit / KiroTrace matrixgraph · suspect links - 3
UX + Ontology Engine
GATE · Design Lead · Tech Lead · PMMachine-readable context, the highest-leverage input to everything downstream.
Use casesCockburnJourney mapsNN/gDesign system + tokensMaterial 3 · DTCGData model3-level ERD · ISO 11179RBAC matrixNIST 359Decision tablesOMG DMNDomain glossaryDDDAPI contractsOpenAPI 3.1 - 4
Code Engine
GATE · Tech Lead + senior devsAI drafts, a human approves, with provenance on every line.
ADRsNygardPR + AI provenanceConventional CommitsDefinition of DoneScrumCoding standardsagent-consumableTest planwith the code - 5
QA Engine
GATE · QA LeadMutation testing is the umpire, coverage doesn't prove the tests assert anything.
Test casesISO 29119Defect reportsCompletion reportexit criteriaGo / no-gorelease readiness - 6
Delivery
GATE · PM + ClientAcceptance is the legal trigger, it releases payment, starts the warranty, transfers IP.
Release noteschangelogUAT + acceptance certcontract-bindingRunbook + rollbackHandover
Tamper-evident evidence, one seal that satisfies contract acceptance, SOC 2 CC8.1, and the EU AI Act Article 14 at once. The artifacts are the review surfaces. The gates are the product.
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. Perfect training pairs.
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
Fine-tune
layer
240
projects
8
years
Every pair poured through, distilled
AGENTS
Units that actually work
Down at the most atomic level of a codebase, what they came to call infinite control.
240 PROJECTS · 8 YEARS · EVERY PAIR INTACT
This is the moat nobody else has.
Not a demo. A measured capability , carrying quality, quantity, features and standardisation. The loaf could finally be promised.
Then the honest flinch: maybe it only works for code. So we picked the least code-like domain we could find — sales, built an ontology of its nouns and its verbs across every data source, and ran the benchmark again.
Spec → Code
BENCHMARKaccuracy translating a spec into working code, the number that turned a hope into a promise.
Model vs Model + Ontology
SALESSame frontier model, one domain it was never built for, with the harness, and without it.
MODEL ALONE
baseline
MODEL + ONTOLOGY
+5% better outcome
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. Software was just the first proof; sales was the second. The blueprint is the constant, the domain is not.
Your data in, an expert-defined ontology on top, atomic decomposition of the work, and fine-tuned harnessed agents on top of that. 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.
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 gate emits tamper-evident evidence. The same trail serves contract acceptance, SOC 2 CC8.1, and EU AI Act Article 14 at once, one record, three obligations.
The first milestone is time-to-approved-spec: a reviewed, traceable spec.md, produced fast. Value shows up as an approved artifact, not a promise.