AI implementation and managed services

Put AI to work that earns its place.

Metacto implements AI in your recurring workflows and manages it after launch, so it stays accountable, measurable, and improving. Start with one workflow connected to your systems. Add more as the results justify it.

45 minutes with our AI experts to find your highest-value opportunity and a practical next step. No preparation required.

Talk to an expert See an AI agent at work

What you can hold us to

Three things that are true of every agent we deploy

Production, not pilots

Agents 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

Agents 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.

What it is

A small workforce of AI agents, each doing one specific job

An agent 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.

Inputs

Invitation to bid, plan set, project data

The agent

Bid & RFP AI Agent

Construction

Prepare the scope of work and the cost-code bid forms

Systems

The project management and estimating tools it is scoped into

Human oversight

The project manager reviews and owns the final package

Output

A drafted bid package, waiting when the PM sits down to it

Operating standard

Completeness, accuracy against the plan set, and every required approval present. Written down and measured, so the agent can be held to it.

The unit of value

Three agents, three different jobs

You add them as the work justifies them, and the workforce grows month over month.

Bid & RFP AI Agent

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 Agent

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 Agent

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.

Where it fits

Where would an AI agent 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 an agent 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 →

The same work, before and after an agent owns it.

Nothing about the job changes. What changes is who assembles it, and how much of your team's day it takes.

Today — manualToday

Someone gathers the inputs, chases what is missing, rebuilds the same context each time, and formats the result before anyone can act on it.

After — agentic workflowWith an AI agent

The AI agent assembles the work and brings it forward ready to review. Your team makes the judgment call, and the record lands back in the system it came from.

Why Metacto

Four reasons this works where generic AI stalls

Built around your business

Will this fit how we actually work? Agents are shaped to your real processes, terminology, rules and approval paths.

Connected to the work

Will it actually do the job? Agents 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.

How it compounds

Start with one agent. 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 agents have earned their place, each one landing on the business context the last one built.

LaunchFirst engagement

Quality inspectionOperations

One agent, one job, live behind human approval from day one.

1 agent

ExpandFollowing months

Quality inspectionOperations

Quality analysisOperations

Demand forecastingPlanning

New agents reuse existing connections and business knowledge, reducing repeated setup.

3 agents

WorkforceAs the evidence supports it

Quality inspectionOperations

Quality analysisOperations

Demand forecastingPlanning

Freight coordinationLogistics

Several functions covered, one platform, one review process.

4 agents

It grows workflow by workflow. Nothing expands until the evidence supports it.

Three tiers of trust

Autonomy is earned, not switched on.

Authority is granted per task type, not per agent, against thresholds you set. Two agents in the same workforce can hold very different permissions, and any grant can be moved back down.

Per task typeActs on its ownHuman approvalNot permitted

Bid & RFP AI AgentConstruction · preparation tasks approved to act

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

Help Desk AI AgentManaged IT · fixes under human review

Triage and classify the ticketActs on its own
Apply an approved fixHuman approval
Change access permissionsNot permitted
Close the ticketNot permitted

The control questions that matter

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.

Ownership

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.

Your environmentYour cloud account, inside your own security boundary.

AI agents
Business context
Operating rules
Integrations
Audit history

Stop Managed AI Services

Metacto Managed AI ServicesThe ongoing service, outside your boundary.

Monitor
Evaluate
Improve

Cut the link and the service ends. Everything inside your environment keeps running, on the last version deployed.

The technology

Powered by Vocion

Open infrastructure underneath your AI workforce.

Every Metacto AI agent runs on Vocion, our open-source Agent Workforce Platform. Vocion provides the operating layer for context, permissions, tools, human review, evaluation, observability and agent lifecycle management.

Metacto keeps the workforce accountable, measurable, and improving. You own the system it runs on.

The open-source operating layer and deployed agents stay yours when Managed AI Services ends. 50 workflow patterns are published and readable before you buy.

Explore Vocion

Your AI workforce

Bid & RFPQuality InspectionHelp DeskDemand Forecasting

VocionOpen-source operating layer

ContextPermissionsToolsHuman reviewEvaluationObservabilityAgent lifecycle

Your cloud account, inside your own security boundary

How it works

Three stages, starting with 45 minutes

The method inside those stages: identify the work, define the agent, teach it the business, connect it to the process, launch with human oversight, measure, improve, expand.

01 · Find the work

Working session

45 minutes, nothing to prepare. We look at where recurring work is costing the most time and margin, and choose the first workflow to implement.

You getThe first workflow chosen where the work actually costs you.

02 · Prove it works

First implementation

One workflow built, connected to your systems, tested on your real cases, and live with human oversight from day one.

You getAI running in your environment, under human approval.

03 · Keep it worth trusting

Managed AI Services

One program covering direction, delivery, operations, and performance: a shared roadmap, committed build capacity, monitoring, and a regular review of results.

You getAI that keeps earning its place.

The commercial model

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 working session. We look at where recurring work is consuming the most time and margin, and choose the first workflow to implement. Nothing to prepare.
What do I buy to get started?: Your first implementation
A bounded engagement on one workflow: we connect it to your systems, test it on your real cases, and put it into production behind human review, with written acceptance criteria. Scoped after the working session, because it depends on the work and the systems it has to reach.
What happens after launch?: Managed AI Services
A 12-month program with one monthly fee covering direction, delivery, operations, and performance for the workflows in scope: a shared roadmap, committed build capacity, monitoring and support, and a regular review of what changed.
How does it expand?: Workflow by workflow, on a roadmap we prioritize together. Each one reuses the context already built. Nothing expands until the evidence supports it.
Who pays for cloud and model usage?: You do, billed directly to your own account at your own rates, because everything 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 agents 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 after the working session against the workflow you actually want to change. Clients in production today are willing to talk about the work; references available on request.

Customer proof

Results from real customer work.

Three engagements running on real systems. Client names withheld where required; references available on request.

Commercial construction

Compliance review agents

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.

½ day → ~10 min

Violation triage cycle per case

+33%

Report audits delivered per month across a 20-analyst team, measured in the first 30 days

about $800K a year, forecast from that period

≈$2.5M

Annual run-rate opportunity across three value tracks

modeled, pending calibration

B2B go-to-market

Lead and outreach agents

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 study

~2 hrs → automated

Personalized research per prospect, lifting a 75-campaign-per-year ceiling

92%

Evaluation result across 24 test cases

2 weeks

From workflow audit to a working prototype on live systems

Education

Discovery and matching agents

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 study

$7.8M

Verified scholarship wins across fewer than 400 active students

client-reported

80%+

Edited essays that convert to wins

client-reported

60%+

Started applications reaching submission

client-reported

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. Agents run inside the tools your team already opens, and we track real usage after launch 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: an agent 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. An agent 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 agent 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 agent into production behind human approval, then expansion as the evidence supports it. Recent launches have put a first agent into production between about one and four months from kickoff.

What happens if we stop paying?

Stop the service, keep the workforce. The agents you have deployed stay in your environment and keep running on their last version. What ends is Metacto's ongoing monitoring and improvement.

How AI takes shape in your business

The expertise that keeps your workforce earning its place.

Metacto brings the consulting, engineering, and ongoing management together around your agents. Explore how each part supports the work.

AI Implementation

Take the right workflow from idea to production.

Find where recurring work costs the most, prove the business case, and build AI into the systems your team already uses.

Explore AI implementation

Custom AI Development

Get the work done inside the tools you already use.

Give preparation, coordination, and follow-up to custom AI connected to your systems, with your people controlling the decisions that matter.

Explore custom AI development

Managed AI Services

Keep AI useful as the business changes.

One program after launch: Metacto sets direction, delivers improvements, runs operations, and reviews performance so changing systems and processes do not leave your team fixing the same problems.

Explore managed AI services

AI Strategy