Build the AI systems your business needs.
Metacto designs and builds custom AI agents, applications, and systems around your business requirements, connected to your data and tools, with evaluation from the start and human review where the work needs it.
Request
"STEM scholarships for first-generation students in Texas, deadlines after January 2027."
Sources searched
- Foundation award pages6/14
- University aid listings3/9
- Eligibility PDFs5/7
- Community foundation sites1/5
35 pages read · 15 kept · 20 ineligible
Structured record · 1 of 15
Lone Star STEM Futures Award
| Field | Extracted | Source |
|---|---|---|
| Award | $5,000, renewableAward page · Overview | Award page · Overview |
| Minimum GPA | 3.0 unweightedEligibility PDF · p.2 | Eligibility PDF · p.2 |
| Residency | Texas residentsEligibility PDF · p.1 | Eligibility PDF · p.1 |
| Field of study | STEM majorsAward page · Who may apply | Award page · Who may apply |
| Deadline | Feb 15, 2027Confirm: FAQ lists Mar 1Two dates found | Two dates found |
20+ years engineering leadership · 100+ products shipped
Every field cited. Every record approved.
Scholarship discovery meant searching the web, reading eligibility rules, and copying details into spreadsheets for each new group of students. Metacto built a structured platform and connected agents that search, extract requirements, enrich, and stage records from one request.
- Runtime checks on every run
- Each record is checked for schema, a cited source per field, and conflicting values before anyone sees it.
- Approval before anything is published
- Administrators verify sources and approve, edit, or reject each record. Students see only approved records.
- Ongoing evaluation across releases
- A test set is rerun on every release, and reviewer edits become new test cases.
- Runtime check · every run
- Pre-action approval · a person decides
- Ongoing evaluation · every release
- 1
Inputs
Sources
Admin requestFoundation pagesUniversity listingsEligibility PDFs - 2
Context and retrieval
What the agent knows
Award schema · 14 fieldsEligibility rulesExisting records for dedupe - 3
Agent with tools
Scoped permissions
search_webread_documentextract_fieldsstage_record - 4
Evaluation checks
Runtime check
- Schema valid14 / 14 fields
- Every field cites a source14 / 14
- Deadline conflict2 dates found · flagged
- 5
Human review gate
Pre-action approval
Administrator approves, edits, or rejects each record. Nothing reaches students before approval.
ApproveEditReject - 6
Write-back
Your systems
Scholarship databaseStudent-facing listAudit log entry
Ongoing evaluation
Every release
- Test set
- 40 sample requests
- Field accuracy
- Tracked per field
- Reviewer edits
- Fed back as test cases
A capability you could not buy, connected and checkable.
- 01
Built around how you work
Designed for your business requirements, not a generic tool's assumptions.
- 02
Work that reaches your systems
Outputs write back into the CRM, ticketing, and tools your team already uses.
- 03
Quality you can check
Every release is measured against test cases your team agreed to.
From architecture to a system ready for rollout.
Each part is documented for whoever maintains the system, your team or ours.
Design
- Architecture, model choices, and the trade-offs behind them
- Context and retrieval: the records, rules, and history the system needs
- The interface people use to review and act
Build
- Agents, workflows, applications, or AI features in your product
- Integrations with CRM, docs, ticketing, email, and internal tools, with scoped access
Prove
- Test cases, an evaluation framework, and a reviewer feedback loop
- Review paths, monitoring, runbooks, and technical documentation
Production rollout, adoption work, and post-launch support are defined in the scope. Scope is fixed or milestone-based, and cloud and model usage is billed to your own accounts.
A defined job first, then releases your reviewers test.
We start from a defined job, the systems it touches, and a technical and business owner on your side.
Define the job
We confirm the job, systems, owner, and success criteria.
A use case, systems map, and agreed test cases.
Design and connect
We design the architecture and connect the context the system needs.
An architecture your IT team has reviewed.
Build and evaluate
We build in releases, each evaluated against the agreed test cases.
A working system your reviewers have tested.
Prepare for deployment
We add review paths, controls, monitoring, and documentation.
A system ready for rollout.
Questions before you build.
Do your AI agent development services require an AI platform project?
No. We build around a specific process or product need, with a defined job, connected systems, and measurable standards.
How do you work with our engineering team?
Your technical owner reviews architecture and code, and your engineers can work alongside ours. Documentation is written for whoever maintains the system.
Are these fully autonomous systems?
Authority is set per task. Systems start with human review and earn permission to act as performance meets thresholds your team sets.
What access do you need, and where does it run?
Scoped access to the systems involved, agreed with IT. The system runs in your own cloud, inside your security boundary, with logs and approval paths.
Who owns the system?
You retain the deployed system and documentation and can keep operating it through your own accounts after a documented handoff.
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Working session
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