Skip to content
Antino
All use cases

Our own playbook · IT services, consultancies, and dev shops

We turned our delivery firm into a function you can rent.

This is how Antino runs itself. We encoded 240 operated functions into a Company Brain, then put two engines on top of it — one that wins and scopes work, one that ships it. You don't hire a team. You name the outcome, and the function ships it.

Outcome: shipped and adopted — not billed hours.Proof: Antino portfolio

Below: the whole pipeline — playable

01 · The problem

A services firm is only as good as the last person who remembers how.

Wins depend on who scoped the deal. Delivery depends on who wrote the code. When that person is on another account — or gone — the proposal is generic, the estimate is a guess, and the new engineer reverse-engineers the repo for three weeks. The firm's real asset is locked in heads, not in a system that can run without them.

02 · How we'd run it

The delivery brain: every brief in, two ways out.

Intelligent decisions. Zero busywork. Every exception, owned.

Work in

Everything the firm already knows.

  • Inbound brief

    Cold email, RFP, referral

  • Past-engagement graph

    240 functions, rated & costed

  • Codebase & tickets

    The live product graph

  • Rates & capacity

    Who's free, what it costs

The delivery brain

Match. Scope. Ship.

  • Capability match
  • Proof assembly
  • Scoping & estimation
  • Outcome commitment
  • Spec generation
  • Delivery triage

every decision logged · every outcome written back

Proposal-ready

~80%

Evidence-backed scope and commitment, drafted in days.

Days, not weeksCited past workScoped to an outcome

Judgment call

~20%

Routed to a partner

Complex cases. Human judgment — with the case pre-packaged:

Full match dossierComparable dealsRisk flags

Grounded in real delivery

Every claim traces to a shipped engagement

Auditable estimates

Scope maps to comparable history

Continuous learning

Every win and loss sharpens the next scope

Client-isolated brains

Your graph stays yours

Scales without bench

More deals, same partners

Shares are illustrative of a typical mature engagement.

03 · The pipeline, end to end

The science of shipping, stage by stage.

This is the actual anatomy of a software engagement at Antino — ten stages, two engines. Drag the depth dial to see what each stage looks like as the agents take on more of the routine work, and hover any stage for a worked example. The ceilings are honest: some of this never stops being human.

Agentic depth — drag it

0%
≈ 0% of routine work absorbedAbout 0% of routine work absorbed2 human-owned gates — at any settingtick on each drop = that stage's honest ceiling; past it stays human
work units on the trackhuman gate — the flow always passes throughabsorbed into the agent lane

Win the work

Revenue OS · win & commit0%

  1. stage 01 · dossier

    Brief intake

    agenthuman

    An RFP or email arrives and becomes structure: requirements, constraints, unknowns.

    • Parses the brief into a structured requirement graph
    • Flags ambiguities and missing decisions for the first call
    • The partner reads what a parser can't — relationship, urgency, politics.

    An EV-charging RFP lands at 4:00 pm

    By 4:09 it's a graph: 14 requirements, 3 flagged unknowns (tariff model, OCPP version, tenancy). The first client call starts at the hard questions instead of discovering them.

    Two days of reading and forwardingStructured by the same afternoon

    click the stage to collapse

  2. stage 02 · dossier

    Capability match

    agent

    Requirements are matched against everything the firm has actually delivered.

    • Searches the 240-function graph for comparable engagements
    • Returns named references with real hours, stacks and ratings

    CSMS + OCPP + wallet → two named references, instantly

    The match surfaces Enercent (13,567 hrs, multi-tenant EV platform) and Lioncharge (OCPP 1.6 CSMS). Not 'we have EV experience' — the exact projects, with receipts.

    A week of asking aroundNamed references in minutes

  3. stage 03 · dossier

    Scoping & estimation

    agenthuman

    The work is broken into workstreams and sized from history, not optimism.

    • Drafts workstreams from comparable delivered scopes
    • Estimates from the hours those scopes actually took
    • The partner adjusts for risk, client maturity, and what the data can't see.

    "Host app + settlement engine" — sized by precedent

    The estimate isn't a planning-poker guess: it's the delivered-hours envelope of the last two comparable builds, adjusted by a partner who knows where this client will be different.

    Planning poker and optimismSized from delivered hours, in days

  4. stage 04 · dossier

    Outcome commitment

    agenthuman owns

    Before anything starts, the engagement is pinned to a named outcome — the metric it must move — backed by comparable history.

    • Assembles the comparables dossier: what this shape took, end to end, the last three times
    • The partner owns the commitment. Always.

    The metric is named before kickoff

    "Live on both stores, first cohort onboarded" — written into the engagement with three comparable deliveries attached. The partner signs a commitment the graph can defend.

    Scope argued clause by clauseOne named metric, agreed up front

  5. stage 05 · dossier

    Proposal

    agenthuman

    An evidence-backed draft where every claim cites a real engagement.

    • Drafts the proposal from the match — claims wired to case studies
    • Assembles the proof pack: outcomes, timelines, named references
    • The partner sharpens the narrative and sends it.

    Claims with receipts, not adjectives

    The draft cites Jobizo's marketplace build (128 weeks, live on both stores) and Revfin's co-lending rails — so 'we can build this' arrives pre-proven.

    A week of deck-buildingEvidence-backed draft in a day

Run the build

Delivery OS · run & ship0%

  1. stage 06 · dossier

    Brain bootstrap

    agenthuman

    Repo, tickets, errors and analytics are indexed into one product graph.

    • Builds the product graph from the client's real artifacts
    • Answers any question about the system with citations
    • Leads verify boundaries, access and what must stay out of scope.

    Day 2: "where is payment retry handled?"

    Answered with the file, the commit, and the ticket that explains why it works that way. Onboarding drops from weeks of archaeology to days.

    4–6 weeks of onboardingProductive in days

  2. stage 07 · dossier

    Spec

    agenthuman

    Features become specs grounded in code that actually exists.

    • Generates specs referencing the real modules and APIs they touch
    • Attaches impact analysis — what breaks, what's affected
    • The architect approves the shape before anything is built.

    "Add UPI mandate" — spec'd against reality

    The spec names the actual payment module and the three services the change touches. No fictional architecture, no surprise on day four.

    Two weeks of workshopsA grounded spec in two days

  3. stage 08 · dossier

    Build

    agenthuman

    Agents handle the routine; engineers own the design.

    • Scaffolding, boilerplate, routine implementation
    • Tests written alongside; changes arrive PR-ready
    • Engineers own design decisions; every merge is human-reviewed.

    The PR that arrived in minutes

    The agent opens a PR with tests for a routine endpoint. The engineer reviews it like any teammate's work — except it was ready before the standup ended.

    Routine work eats the sprintRoutine work arrives PR-ready

  4. stage 09 · dossier

    QA & release

    agenthuman owns

    Regression at machine scale; judgment at the gate.

    • Runs regression packs and visual diffs
    • Pre-triages failures: flaky vs environment vs real
    • The QA lead makes go / no-go. Always a person.

    14 failures, pre-triaged

    11 flaky, 2 environment, 1 real — the human starts at the one that matters instead of spending the morning finding it.

    Days of regression huntingPre-triaged in hours

  5. stage 10 · dossier

    Operate & improve

    agenthuman

    Incidents arrive pre-triaged; every event writes back to the graph.

    • Matches incidents against error history with suggested, cited fixes
    • Watches delivery health, adoption and drift continuously
    • Sev-calls are owned by a named engineer.

    The 2 a.m. incident that took 4 minutes

    The error matches a 2024 Kafka-lag pattern; the suggested fix cites the commit that solved it last time. Forty minutes of Slack archaeology becomes four.

    40-minute Slack archaeologyA cited fix in 4 minutes

Depth bars show the agentic share of routine work at each stage — illustrative of a mature engagement. Design decisions, the outcome commitment and go/no-go calls are human gates, permanently.

04 · One brain, two engines

How the function runs on top of the brain.

Revenue OS

Win and commit

We match an incoming brief against the graph of everything we've already delivered, assemble the proof that closes it, scope it against real historical hours, and draft the proposal — committed to a named outcome, not a bench.

  • Capability match: surface the past projects that prove we can ship this one
  • Proof assembly: pull the architectures, accelerators, and named results that fit the brief
  • Scoping grounded in real delivered hours, not optimistic guesses
  • First-draft proposals generated from the graph, ready for a human to sharpen

Delivery OS

Run and ship

We run delivery on a live product graph of the codebase. Specs are grounded in the actual code, questions get cited answers, and incidents arrive pre-triaged with the likely cause attached.

  • Cited answers from the codebase — no waiting on the one engineer who remembers
  • Specs grounded in real code, not in a wiki that drifted six months ago
  • Pre-triaged incidents: the error, the suspect commit, and the owner, on arrival
  • Onboarding measured in days because the graph already knows the system

05 · What actually changes

The same function, before and after the brain.

MetricBeforeOn the brain
Proposal turnaround2–3 weeks of archaeology1 day, evidence attached
Estimate basisWhoever's optimismRecorded hours of comparable work
Engineer onboarding3 weeks reading the repoDays — the graph already knows it
Incident triageStarts with a searchArrives with the suspect commit

06 · The outcome

240
Functions operated and encoded
221
Clients delivered for
~434k
Hours of delivery in the graph
Days
To onboard an engineer, not weeks

Figures are illustrative unless tied to a named proof engagement.

07 · Live reference · Antino portfolio

240 functions, 221 clients, and roughly 434k hours of delivery — the graph this engine runs on.

See this function on What We Run

More use cases

The same brain, a different function.

Fintech lender / NBFC

We run onboarding and loan origination. Compliant approval, first session.

Outcome: compliant approval in the applicant's first session.

Insurance carrier

We run your claims and underwriting function. Claims decided in minutes.

Outcome: claims decided in minutes, leakage down.

09 · Run a function

Stop renting hours. Start running functions.

Pick the function you want off your plate. We'll map the brain and name the outcome we'd commit to — before you do.

Claims & underwritingMember & benefits adminKYC & onboardingProduct delivery
Talk to usModel your function