Validation agent
Reviews payment capacity and case-file completeness before a human touches them: incomplete files are returned automatically.
Services
AI agents that execute,
not just chat.
A chatbot answers; an agent acts. We deploy AI agents that read your documents and policies, validate information against your business rules and execute the next step of the process — with human oversight and full traceability.
Agents in operation
One agent per decision,
not one bot for everything.
Triage agent
Classifies and prioritizes claims, complaints and requests by severity and SLA — the urgent always comes first.
Policy copilot
Your employees query processes and policies conversationally, with the source cited in every answer.
Audit agent
Generates audit plans from your own policies and verifies compliance against documentary evidence.
Document agent
Assembles the case file, detects missing documents and requests them — no human middle-management.
Human oversight
Every action is logged and critical points always go through a person. The agent executes; you decide.
How we work
From written policy
to an agent in production.
01
Diagnosis
We pick the process where an agent creates the most value — repetitive decisions, high volume, clear rules.
02
POC in 2–3 weeks
The agent working with your real documents, policies and cases, at a fixed cost.
03
Supervised production
Deployment with gradual autonomy: first it suggests, then it executes with approval, then it executes and reports.
04
Evolution
We extend the agent's scope and connect neighboring processes.
Real results
Related case studies
Pilot underwayColombian insurer — claims
AI claims management: intake and triage from 2–3 days to 30 minutes
Pilot with a Colombian insurer: AI reads the claims inbox, classifies attachments, checks coverage and files each claim by priority in under 30 minutes.
2–3 days → 30 minclaim intake and triage40% → 85%complete files at first filing
Read the case In productionCompany — compliance and audit
AI agents on corporate policies: audit plans in minutes
A company loaded its corporate policies and built two AI agents: one generates audit plans, the other answers employee questions with cited sources.
2agents on the same policy baseHours → minutesdrafting an audit plan
Read the case In validationFinancial institution — credit origination
AI payment capacity analysis: from days to minutes
Concept under validation: AI extraction of bank statements and pay stubs to analyze payment capacity before the file reaches the analyst.
Days → minutesdocumentary payment capacity analysis100%files with supporting documents validated before the analyst
Read the case FAQ
What we get asked
before starting
How is an AI agent different from a chatbot?
A chatbot converses; an agent executes tasks: it reads a case file, validates against rules, consults a policy, requests missing documents or prepares an audit plan. Conversation is just one of its interfaces.
Can I audit what the agent does?
Yes. Every action, decision and consulted source is logged with full traceability — a non-negotiable requirement in the regulated sectors we work with.
Which AI models do you use?
The leading models depending on the case (OpenAI, Anthropic, Google), without locking your operation to a single provider. The architecture lets you switch models without rebuilding the solution.
When do you NOT recommend an agent?
When the process is simple enough for traditional automation, or so critical that it requires a human decision at every step. That judgment is part of the diagnosis — we don't sell agents for their own sake.
Your operation has dormant time.
Let's wake it up.
Book an initial diagnostic. We leave the meeting with at least one concrete improvement opportunity identified.