Autonomous AI your board can actually sign off on.
A staffed, governed organization in your own infrastructure: one chain of command, hard gates, and a record behind every signature.
The agents are ready. The signatures are not.
This is built for enterprise IT organizations, in any sector. Regulated status, AI that will not scale past a pilot, and architecture older than the problem are what sharpen the need; none of them is a condition of it. What the board is holding up is a governance problem, not a technology problem. The agents can already do the work. Four people have to sign before it reaches production, and today not one of them has what they would need to.
The CISOControl over what an agent can touchNot signed✓ Signed
The CFOA hard cap in the execution pathNot signed✓ Signed
Risk and auditA forensic record, by defaultNot signed✓ Signed
EngineeringA kill switch, at every levelNot signed✓ Signed
0 of 4 · blocked4 of 4 · cleared to ship
01 — Why nothing ships
Four people have to sign. None of them can.
The CEO wants autonomous AI doing real engineering work. Before any of it reaches production, four people put their names on it. Every one of them is missing the one thing that would let them, in the stack they have today.
The CISONo control over what an agent can touch.no touch-scope
The CFOModel spend is unbounded by default.no spend cap
Risk and auditNo forensic record when something goes wrong.no record
EngineeringNo kill switch, at any level.no kill switch
>40%
of agentic AI projects will be canceled by the end of 2027
Gartner · 2025
~21%
of enterprises have a mature agentic-AI governance model; four in five do not
Deloitte · State of AI 2026
$1.44
cost per shipped change, queried from our own instance's ledger rather than modeled
SpeyAI · own instance
$23.41
what one governed change cost against the $18 to $34 band quoted before it started
SpeyAI · own instance
The adjacent categories, and what this does instead.
Several kinds of product sit next to this one, and each is good at the job it was built for. What follows is what a governed org does, stated against each of those jobs.
The adjacent categories · what this does
01Beside agent identityIdentity platforms govern who an agent is and how it signs in. This governs what a change touched, what it spent, who approved it and what shipped, and records all four against the role that acted.
02Beside governance platformsThose platforms discover, monitor, score, evidence and enforce policy on what agents do. This staffs the organization that does the work, so the controls and the output come out of one architecture and one ledger.
03Beside coding agentsAgents produce the work. This puts the work under a chain of command: defined seats in every discipline, a reviewing seat that is never the writing seat, and a cap checked in the execution path before the model is called.
04Beside building it yourselfEntirely possible, and then the governance layer is a product your own team maintains forever instead of one you buy.
Each of those is good at the job it was built for, and a serious enterprise will end up holding two of them. That is the actual position most are in: integrating two purchases into something neither vendor sold them, where the integration is the part that fails.
The agent technology exists. This staffs the work, and gates it in the execution path.
02 — What it actually is
Not another agent. The company they work for.
SpeyAI installs a governed organization inside your own infrastructure: defined seats under one chain of command, answering five questions on every action. What it touches, what it spends, who approves, what ships, what gets logged. All five are enforced through the pipeline, and a new instance ships nothing without a human signature.
The organization · cutaway
01The workforceDefined seats in every discipline, under a real chain of command.
02The rulesSacred do-not-touch paths, hard spend caps, and a kill switch at every level.
03The enginesThe pipeline that runs intake to shipped, and recovers work that fails.
04The connectionsIt plugs into the version control, database, and model accounts you already own.
05One screenThe whole organization on a single console, every surfaced item with its action inline.
The disciplines are fixed. The domains are yours.
Two things decide what a governed org ships. The disciplines that read every change are the same in every deployment. The domains it works in are not.
Every unit of work crosses the same review bank before it can leave the org, and the seat that wrote a change is never the seat that reads it. Research frames the Brief. The seats build. The review bank reads every change. Preflight opens the pull request in your own repository, and a new instance holds it for a human signature.
Staffed for your domains
Disciplines are constant. Pods are not. A deployment is staffed for the work you actually have, and a specialty domain ships as a persona pack.
01BaseHardened role templates, shared by every deployment.
02YoursYour domains, your titles, your rules on top.
03EarnedWhat production teaches, appended as standing doctrine.
Five agents or five thousand. One chain of command.
03 — Runs on your own infrastructure
Your building, your data.
The organization installs inside the perimeter you already run and uses the accounts you already pay for. State lives in your own Postgres, with row-level security on every table. When the org runs inside AWS, Azure, or Google Cloud, it can sign in with that cloud's own managed identity, so there is no stored database password. Code and data never leave, and there is exactly one outside connection: the release channel that delivers SpeyAI itself, outbound and initiated by you.
The console · detected configuration
Your version control, your object store, your model account, each named beside the source the console read it from.
And it builds for your warehouse.
SpeyAI builds and maintains the code that runs on your lakehouse: pipelines, models, SQL, infrastructure. It does not read from or connect to your warehouse. This is a build capability, not a data connection, and the organization is fluent in the major lakehouse platforms.
Development capability
Builds and maintains your data platform
Beyond running on your own infrastructure, the org is fluent in the major lakehouse platforms. It writes and maintains the code that runs on them: pipelines, models, SQL, and infrastructure. This is a build capability, not a data connection. The org does not read from or connect to your warehouse.
Databricks
Snowflake
BigQuery
Microsoft Fabric
04 — Bringing it in
It reads your repo and drafts its own rules.
Onboarding is not a form to fill out. The organization reads your code and drafts its own configuration: the sacred do-not-touch list, the rules, the personas, the org sizing, the budgets. Your people ratify every line. Your partner implementer amends the draft, your CISO signs the sacred-file registry. Nothing holds until a person puts their name on it.
No authority on day oneDefault 14 days · observe and propose only
01It draftsreads your repo · proposes config
02Proposes onlyfull pipeline · zero merges
03Awaiting youthe record accumulates
04You graduate ita human click · now live
Not one merge happens without a human click. It graduates when you decide it has earned autonomy, never when a timer runs out.
Then it serves probation. For a default of fourteen days it observes and proposes only. The full pipeline runs, the full audit trail accumulates, and not one merge happens without a human click. It graduates when you decide it has earned autonomy, never when a timer runs out.
The console · a Brief awaiting ratification
Work arrives as a Brief with its scope and a cost band, and none of it starts until a person ratifies it.
Additive infrastructure. The same motion as adding Sentry or Datadog.
05 — Governed spend
One ledger. Two jobs.
A hard cap is checked in the execution path before the model is ever called. A runaway loop stops at the ceiling, and the card simply stops working. The same micro-USD ledger then reports what the work cost against the band quoted before it started. Prevention and proof from one record.
One Brief crosses the pipeline's enforcement points while the spend counter runs. The five governance questions are answered on the way to production, the record written as it goes. A runaway gets stopped twice; the same work ships for $23.41 against a band of $18 to $34.
Brief SPY-4412 · live$0.00
01Scope approved
02Budget capped
03Touch-scope enforced
04Independent review
05Human merge
What the same team can ship
PreventionCaps live in the execution path. Unbounded spend is structurally impossible, not caught on a monthly report.
CapacityThe same ledger prices a shipped change against a labeled benchmark of $1,000 per merged pull request, which you set yourself as a fully-loaded human cost. Read it as capacity: the question it answers is how much more of the backlog the team you already have can clear in a quarter, not what a person costs. The operator stays the approver either way.
A labeled assumption, not a measured saving. Nothing here is a headcount claim.
This is also the argument for the person who has to sponsor it rather than tolerate it. Governance gets bought by risk and security; throughput gets bought by engineering, and a purchase that satisfies one of them stalls at the other. Controls are what make unattended work safe enough to leave running, so the same architecture that lets the CISO sign is what lets the team you already have take on more of the backlog. One purchase, both budgets.
How it is licensed
The shapeA self-hosted license for the software that installs in your environment, a subscription that carries releases and support, and certification for the implementers who deploy it. Priced per deployment.
Why no figure is hereWhat a first deployment covers is the thing being priced, so the number comes out of the briefing with your partner implementer rather than off a page.
Governed spend is efficient spend.
06 — What an auditor sees
The record writes itself.
The forensic record is a by-product of the chain of command. Every approval, diff, spend, and merge is already an artifact, recorded against the role that produced it, not a debug log switched on after an incident.
Audit record · one action
Role
senior-backend-engineer
Action
merge · brief SPY-4412
Cost
$23.41
Approved by
a human signature
Recorded
forensic · by default
Postures supported
SOXSOC 2GDPRHIPAA
Supported audit postures, never certifications.
What can an agent touch?
You define the do-not-touch paths and the organization structurally cannot write to them. Sacred paths are enforced on the diff, so the answer is architecture rather than a policy somebody has to police. Your CISO signs that registry during onboarding and owns it afterwards.
Where is the kill switch?
One control stops all autonomous work at once, and it is there from the first day rather than a feature somebody wires up before going live. Caps and auto-stop breakers sit at every level beneath it, so a single runaway halts without halting the organization.
Does our code or data leave?
No. The org runs on your cloud, commits to your version control, and calls your own model account. It stores state in your managed Postgres (RDS, Aurora, Azure Database, or Cloud SQL), with row-level security on every table. The only outside connection is the release channel that delivers SpeyAI itself, outbound and initiated by you.
What stops a runaway from spending?
A per-task cap is checked in the execution path before the model is called, not reconciled on an expense report after it. A runaway loop stops at the cap. The card simply stops working.
Can it ship something nobody reviewed?
No. The seat that writes a change is never the seat that reviews it, and never the one that merges it. A new instance holds every merge for a human signature and keeps doing that until you graduate it out of probation. After graduation a documentation-only change can merge on its own when every required gate is green. Code reaches production under a human signature unless you deliberately switch on the small-change window.
What does an auditor see?
Every action recorded against the role that took it: who acted, what changed, what it cost, who approved. The record is forensic by default, not a debug log switched on after an incident.
What kind of work does it actually ship?
Work is scoped as a Brief, built by the seats that own it, and read by every discipline the change touches before it leaves the org: architecture, security, QA, code quality, design, UAT, voice, export, data, and documentation. The disciplines are the same in every deployment. The domains are staffed to the work you have.
What will it not do?
It builds and maintains the code that runs on your data platforms; it does not read from or connect to your warehouse. It runs on your own model account, and only on models certified against the governed org, which is a governance act with evidence behind it rather than a compatibility checkbox. Changes to your systems land as reviewed pull requests in your own repository; advisory work such as daily briefs, periodic audits, and customer health reports lands as a recorded artifact you can query rather than a change to your code.
07 — Next steps
See it in your own infrastructure.
The briefing
Prepared for a named recipient
A working session on the architecture, the governance model, and a first scope in your own environment. Nothing here is self-serve; every briefing is prepared.
