Build an AI workforce that earns its place.
Metacto builds AI roles for recurring work, connects them to your systems and operating rules, and manages them in production. Start with one role behind human review. Add more as the results justify it.
45 minutes. No prep. We map the first one or two roles with you.
Three things that are true of every role we deploy
Production, not pilots
Roles are connected to real systems and measured against a defined job, with a written operating standard they can be held to.
Human-controlled from day one
Roles begin behind human review and earn authority task type by task type, against thresholds you set and can move back down.
Owned by you
The deployment and the business intelligence it accumulates stay inside your own environment.
Production outcomes from live engagements are further down this page.
A small workforce of AI roles, each doing one specific job
A role is not a chatbot, and not a seat of software. It is one piece of recurring work with a defined job, the systems it needs to finish it, and a person who stays in charge of the outcome. Here is one, end to end.
Invitation to bid, plan set, project data
Bid & RFP AI Role
ConstructionPrepare the scope of work and the cost-code bid forms
The project management and estimating tools it is scoped into
The project manager reviews and owns the final package
A drafted bid package, waiting when the PM sits down to it
Completeness, accuracy against the plan set, and every required approval present. Written down and measured, so the role can be held to it.
Every role has the same shape. Only the job changes.
Three roles, three different jobs
You add them as the work justifies them, and the workforce grows month over month.
Bid & RFP AI Role
Commercial construction. Reads invitations to bid and plan sets, drafts the scope and cost-code forms, and stages the subcontractor RFP. The project manager reviews and owns the final package.
Quality Inspection AI Role
Manufacturing. Guides required inspection steps, captures evidence at the point of work, and flags anything outside the expected sequence. The quality team owns exceptions and approval.
Help Desk AI Role
Managed IT. Handles routine tier-one requests using approved fixes and escalation rules. Anything outside its authority arrives in the service desk with the work already prepared.
Three roles at three different tiers of trust. Client names withheld; references available on request.
Where would an AI role fit in your business?
Not by department, but by the shape of the work. Most of the recurring work that survives a growing business falls into one of six kinds, and each one is somewhere a role can take a job off your team.
Work that prepares
Proposals, reports, briefs, estimates, documentation.
Work that checks
Quality reviews, compliance checks, reconciliations, audits.
Work that chases
Approvals, missing information, follow-ups, exceptions.
Work that processes
Documents, requests, tickets, transactions.
Work that monitors
Changes, thresholds, status, operational conditions.
Work that coordinates
Multi-step processes across people and systems.
Each of these maps to specific use cases by industry.Browse by industry →
Four reasons this works where generic AI stalls
Built around your business
Will this fit how we actually work? Roles are shaped to your real processes, terminology, rules and approval paths.
Connected to the work
Will it actually do the job? Roles run inside the processes where the work already happens, not in a tool sitting beside them.
Yours to keep
Is it ours? The deployment, and the business context it builds up over time, stay with you.
Managed after launch
Who keeps it worth trusting? Metacto monitors, evaluates and tunes it in production.
Start with one role. Add the next when the work justifies it.
A workforce is not something you buy on day one. It is what you have after a few roles have earned their place, each one landing on the business context the last one built. Below is how one live engagement sequenced it.
One role, one job, live behind human approval from day one.
1 roleNew roles reuse the context already built, so each one costs less to stand up than the first.
3 rolesSeveral functions covered, one platform, one review queue.
4 rolesThe workforce grows role by role. Nothing expands until the role before it has earned it.
Autonomy is earned, not switched on.
Authority is granted per task type, not per role, against thresholds you set. Two roles in the same workforce can hold very different permissions, and any grant can be moved back down.
- Draft the scope and cost-code packageActs on its own
- Stage the subcontractor RFPActs on its own
- Submit the bidHuman approval
- Commit a priceNot permitted
- Triage and classify the ticketActs on its own
- Apply an approved fixHuman approval
- Change access permissionsNot permitted
- Close the ticketNot permitted
- Which task types are allowed to act without a human?
- What evidence moves a task type up a rung?
- Who owns the threshold, and who can move it back down?
Nothing earns more room until the evidence supports it.
Stop the service, keep the workforce.
The workforce runs inside your environment, and it gets more valuable as it learns how your company works. That part is yours, permanently.
- AI roles
- Business context
- Operating rules
- Integrations
- Audit history
Stop Managed Operations
- Monitor
- Evaluate
- Improve
Cut the link and the service ends. Everything inside your environment keeps running, on the last version deployed.
Powered by Vocion
Every Metacto AI role runs on Vocion, our open-source Agent Workforce Platform. Vocion provides the operating layer for context, permissions, tools, human review, evaluation, observability and role lifecycle management.
Metacto operates the workforce. You own the system it runs on.
Because the operating layer is open source, the workforce is not dependent on Metacto continuing to operate it. 50 workflow patterns are published and readable before you buy.
Explore VocionThree stages, starting with 45 minutes
The method inside those stages: identify the work, define the role, teach it the business, connect it to the process, launch with human oversight, measure, improve, expand.
AI Workforce Review
45 minutes, nothing to prepare. We look at where recurring work is costing the most time and margin, and map the first one or two roles around it.
You getThe first one or two roles mapped to where the work actually costs you.
Launch and Prove
The first roles built, connected to your systems, and live with human oversight from day one.
You getRoles running in your environment, under human approval.
Managed Operations
Metacto watches the workforce in production, checks how each role is performing, and tunes it as your business changes.
You getA workforce that keeps earning its place.
How you buy it
The sequence, in the order it happens, so your finance team can see the shape of the deal before anyone books a call.
- What happens first?
- No cost
A 45-minute AI Workforce Review. We look at where recurring work is consuming the most time and margin, and map the first one or two roles around it. Nothing to prepare.
- What do I buy to get started?
- Launch and Prove
A bounded engagement that builds the first roles, connects them to your systems, and puts them into production behind human review. Scoped at the review, because it depends on the work and the systems the role has to reach.
- What happens after launch?
- Managed Operations
A 12-month agreement covering an agreed set of active roles. Metacto monitors the workforce in production, evaluates how each role is performing, and tunes it as your business changes.
- How does the workforce expand?
Role by role, as each business case is proven. New roles reuse the business context already built, so each one costs less to stand up than the first. Nothing expands until the role before it has earned it.
- Who pays for cloud and model usage?
You do, billed directly to your own account at your own rates, because the workforce runs inside your cloud. It is not marked up through us.
- Can procurement use AWS Marketplace?
Yes. You can procure through the AWS agreement you already have, so this goes through a channel your finance team has already approved.
- What happens if we stop paying?
Stop the service, keep the workforce. The roles you have deployed stay in your environment and keep running on their last version. What ends is Metacto's ongoing monitoring and improvement.
Figures are set during the AI Workforce Review against the roles you actually want. Clients in production today are willing to talk about what the roles do; references available on request.
What happened after the roles went live.
Three engagements running on real systems. Client names withheld where required; references available on request.
Compliance review roles
Analysts reviewed inconsistent payroll files, interpreted wage determinations, triaged violations and drafted notices. Eleven governed workflows now run inside the client's own platform, with citations, review gates and audit trails.
Read the case studyViolation triage cycle per case
Recovered analyst capacity across 20 analysts, about 8.3 hours each per week
Annual run-rate opportunity across three value tracks
modeled, pending calibration
Lead and outreach roles
Enrichment, qualification and personalized research sat across five systems and ran about two hours per prospect. A governed prototype shipped on the client's live revenue stack, with approval gates ahead of every send.
Read the case studyPersonalized research per prospect, lifting a 75-campaign-per-year ceiling
Evaluation result across 24 test cases
From workflow audit to a working prototype on live systems
Discovery and matching roles
Scholarship discovery meant searching the web by hand and reading eligibility rules into spreadsheets. An orchestrated agent workflow now searches, extracts requirements, enriches and stages reviewable records for admin approval.
Read the case studyVerified scholarship wins across fewer than 400 active students
client-reported
Edited essays that convert to wins
Started applications reaching submission
Figures labelled as modeled are business cases built from the client's own baseline, not realised results. Figures labelled client-reported are the client's own measurement.
Before you book
Is this system watching our people?
No. It watches the work, not the worker. If a document is missing or a step happened out of order, the flag lands on that work item. There are no per-person scorecards, and nothing here is built to rate individuals.
Will our team actually use it?
Only if it is faster than what they do today, so that is the bar we build to. Roles run inside the tools your team already opens, and we track real usage from week four rather than assuming it.
We already use ChatGPT and Copilot. How does this fit?
Those help a person write, research and think faster. This is different: a role that does one defined job in your systems and hands the result to someone on your team. Most clients keep both, and we can run on the AI vendor agreement you already have.
Our data is a mess. Are we ready for this?
Everybody has data and nobody has clean data. Building the connected business context AI needs is part of the work rather than a prerequisite to it. Where a larger data project is genuinely needed, we scope it with you.
What about security and governance?
Everything runs inside your own cloud account. A role can read what its job needs, but it can only change something through a human approval step until you decide it has earned more room. Access is scoped system by system, and every action it takes is logged.
How long before the first role is running?
It depends on the work and the systems it has to reach, so we scope it at the review rather than quoting a standard number. The shape is consistent: a bounded launch that puts the first role into production behind human approval, then expansion as the evidence supports it. Recent launches have put a first role into production between about one and four months from kickoff.
What happens if we stop paying?
Stop the service, keep the workforce. The roles you have deployed stay in your environment and keep running on their last version. What ends is Metacto's ongoing monitoring and improvement.
Find the first piece of work worth giving back to your team
45 minutes, nothing to prepare. We look at where recurring work is consuming the most time and margin, and map the first one or two AI roles around it.
Thank you!
We'll be in touch within one business day to discuss next steps.
Explore Opportunity Mapping