Turn recurring work into AI roles your team can rely on.
Our AI agent development services turn recurring work into AI roles built around your processes and systems. As part of Metacto Managed AI Workforce, we connect the business context, build the agent or workflow, and launch with human oversight where the work needs it.
Start with an AI Workforce Review: a 45-minute conversation to find the first one or two roles for your team. Nothing to prepare.
Built for teams ready to turn a high-value workflow or operational role into a live AI system with human oversight, measurable outputs, and production controls.
20+ years engineering leadership · 100+ products shipped · production AI systems across Sales, Ops, Support
Why most AI projects never become operational
AI projects stall when demos are not connected to real systems, business context, review paths, or daily workflows.
Pilots never reach production
Teams run demos for months, but nothing actually operates inside the business. Leadership wants leverage; the organization has screenshots.
Platform-first projects stall
Large AI platform plans turn into long roadmaps before a single workflow changes. Operational value stays months away.
Context is fragmented
CRM, docs, email, Slack, tickets, calls, and tribal knowledge remain disconnected. AI produces generic outputs because it cannot see how the business actually works.
No operational path
Outputs stop at drafts, scripts live outside the workflow, and teams keep copy-pasting between tools instead of running a production system.
Move work across your systems without the manual coordination.
Metacto connects your tools so agents can prepare the work, route reviews, and return results to the right system, without your team moving information between each step.
Disconnected tools, manual coordination, and AI outputs that still require people to stitch the work together.
Connected systems in. AI agents and workflows execute repeatable work. Humans review where needed. Results write back into the systems your team already uses.
What AI Agents & Workflows delivers
Production AI systems built around a specific workflow or operational role, fully integrated, measurable, and ready for daily use.
- Production AI workflow or role-based agent
- Integrated with source-of-truth systems such as CRM, docs, ticketing, email, and internal tools
- Human review and approval paths for material actions
- Review surfaces and write-backs inside existing tools
- Evaluation framework and feedback loop
- Monitoring, alerts, and accuracy dashboards
- Runbooks for the team that owns the system
- Foundation for future workflows, agents, and AI Operations
Two deployment patterns. One Operational AI foundation.
AI Workflows
Best when work moves across people, tools, approvals, handoffs, or routing logic.
- Proposal generation
- Renewal prep
- Support triage
- Reporting workflows
- Intake-to-routing
AI Agents
Best when repeatable knowledge work depends on gathering context, preparing outputs, and supporting decisions.
- Account research
- Executive briefings
- Customer success analysis
- Support analysis
- Operational reporting
An AI role at work: renewal preparation
Arrive at the renewal conversation prepared.
Metacto connects account history, open issues, and next steps into a brief your account manager can review before the call.
Scroll across to follow the full workflow →
How AI Agents & Workflows engagements start
These are the delivery steps behind Launch and Prove: select the work, connect its business context, and launch the role inside your systems.
Select the work
We confirm the job, systems, and success criteria. When several opportunities need deeper comparison, Opportunity Mapping helps choose the first.
A clear use case, systems map, owner, and success criteria.
Context Engineering
We connect systems, structure business context, and build the foundation AI needs to operate reliably.
A context layer ready for production deployment.
Production deployment
We build the agent or workflow, integrate review paths, add controls, and launch inside the tools where work already happens.
A live Operational AI system producing measurable outcomes.
Which operational opportunity should become a production AI system first?
45 minutes. We look at where recurring work is costing the most time and margin, and map the first one or two roles around it. Nothing to prepare.
Scholarship discovery, ready for an administrator to review.
Securing Degrees · Education
The problem
Scholarship discovery meant searching the web, reading eligibility rules, and copying details into spreadsheets. Staff repeated that research for each new group of students.
The outcome
Metacto built a structured platform and connected agents that search, extract requirements, enrich, and stage scholarship records from one request. Administrators verify the sources and approve records before students see them.
Common questions
Do your AI agent development services require an AI platform project?
No. AI Agents & Workflows is the implementation capability behind Metacto Managed AI Workforce. We build around a specific business process or role, with a defined job, connected systems, and measurable operating standards.
What is the difference between an AI workflow and an AI agent?
AI workflows are best for structured handoffs, routing, approvals, and repeatable processes. AI agents are best for repeatable knowledge work where the system gathers context, prepares outputs, and supports decisions. Both use the same Operational AI foundation.
Are these fully autonomous systems?
Authority is set per task type. Roles start with human review and can earn permission to act as measured performance meets thresholds your team sets. Your team can change those permissions at any time.
What systems do you integrate with?
Common systems include CRM, email, docs, Slack, ticketing, call transcripts, cloud storage, BI tools, and internal applications.
Where does it run?
Your AI roles run in your own cloud, inside your security boundary with scoped access, logs, and approval paths. The deployment and the business intelligence it builds stay yours, including when Managed Operations ends.
What happens after launch?
Managed Operations keeps your workforce accountable, measurable, and improving after launch. Continuous AI Operations provides the monitoring, evaluations, tuning, and support behind that ongoing relationship.
Is this the right fit?
Good fit
- A high-value workflow or operational role has already been identified
- Manual coordination or repeatable knowledge work is slowing execution
- AI pilots have failed to reach production
- The system needs to integrate with real business tools
- Human oversight and measurable outcomes matter
Not a fit
- Broad AI strategy exploration without a clear operational opportunity
- Looking for a generic chatbot or off-the-shelf automation tool
- No internal owner for adoption
- No appetite for putting AI into production alongside the team
Adding AI to an existing app?Explore AI features for your product →
How your AI workforce takes shape
Build the right role. Keep it working for your team.
An effective AI workforce needs a clear job, reliable business knowledge, and ongoing improvement. These capabilities support the build.
AI Consulting & Implementation
Take the right workflow from idea to production.
Work with Metacto to identify the workflow worth changing and carry it from a practical business case into production.
Explore consulting and implementationManaged Operations
Keep your AI workforce useful as the business changes.
Keep your deployed agents useful as systems and workloads change, with monitoring, evaluations, and improvements managed by Metacto.
Explore continuous AI operationsOpportunity Mapping
Know where to start when the choice is not obvious.
When you need a closer look, compare the value and readiness of your workflows before committing to a build.
Explore Opportunity MappingContext Engineering
Give agents the knowledge to get the work right.
Give your agents the records, rules, and customer history they need to prepare work your team can use.
Explore Context EngineeringOne workforce. Built and managed around your business.
See how the roles, ownership, and ongoing improvement fit together.
See the jobs an AI role can take off your team's plate.
Explore all industries →Construction
Get project paperwork out of the way.
Bids, RFIs, and change packages prepared from the records your team already uses.
Explore workflowsManufacturing
Keep missing information from slowing production.
Inspection evidence and exception records ready for the people who make the call.
Explore workflowsMSP & IT Services
Give technicians more time for difficult requests.
Account context, routine steps, and escalation details brought into the ticket.
Explore workflowsSee what it takes to put an agent into daily use.
From use case to production workflow
The systems, context, evaluations, and rollout decisions behind a working AI role.
Read the implementation guide about From use case to production workflowSet clear limits on agent actions
Define which tasks can act, which wait for approval, and how permissions change.
Explore permissions and approvals about Set clear limits on agent actionsTest the work before the rollout
Use real examples, edge cases, and reviewer feedback to check the output.
Read the testing guide about Test the work before the rolloutAI Workforce Review
Find the first job an AI role could take off your team's plate.
45 minutes. We look at where recurring work is costing the most time and margin, and map the first one or two roles around it. Nothing to prepare.
Your Review request is received.
Our team will follow up to arrange your 45-minute AI Workforce Review. Nothing to prepare.
Explore Managed AI Workforce