AI Agents & Automation

Overview

What we do

We help teams assess and build AI assistants for knowledge search, document processing, customer support, and workflow routing. Retrieval-augmented generation (RAG) connects responses to approved information; controlled tools connect an assistant to business systems. We evaluate quality, privacy, cost, and failure cases before expanding automation, with human approval for consequential actions.

Who this helps: Teams with repetitive document or support workflows and an approved source of business information.
How we approach your project: We select a narrow use case, agree evaluation examples and access rules, build a pilot, test unsupported answers and unsafe actions, then review monitoring and operating costs before production.

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What you get

Production-ready AI agent or pipeline
Integration with your existing systems
Knowledge base & vector store setup
Monitoring & evaluation framework
Documentation & training guide
Ongoing model maintenance support

Capabilities

What we deliver

These capabilities can be scoped to your needs. We agree features, integrations, technology, and support terms before implementation.

Knowledge Assistants & RAG

Search approved documents with source references, access-aware retrieval, and a clear response when evidence is missing.

Controlled Agent Workflows

Task extraction and routing with restricted tools, human approvals, and activity logs rather than unrestricted autonomy.

Document Processing

Extract and classify information from files, validate required fields, and route uncertain results for review.

Customer Support Assistance

Draft replies grounded in your knowledge base, with escalation and a clear distinction between AI and human support.

Privacy & Safety Controls

Data minimization, permissions, retention decisions, and tests for prompt injection and unintended tool use.

Evaluation & Observability

Representative evaluation sets, trace review, latency and cost tracking, and regression checks as prompts or models change.

Technologies

Built with proven tools

Example tools and practices we consider. The final stack follows your requirements, hosting constraints, and maintenance needs.

Model APIs Python FastAPI Retrieval & Vector Search PostgreSQL Evaluation & Tracing

Our Approach

How we work

A structured, transparent process from first call to production deployment.

Discovery

We understand your goals, users, and constraints before proposing any solution.

Design

Architecture, wireframes, and a clear plan — reviewed and signed off before we build.

Build

Iterative development with demos and feedback at every milestone.

Handover

Test results, documentation, and launch or support responsibilities agreed for your engagement.