AI Agents
We design and deploy LLM-powered agents that go beyond chat — executing multi-step tasks, integrating with your existing systems, and operating with full audit trails.
What we deliver
Six areas of focused delivery within the AI Agents practice.
LLM Integration & Fine-tuning
Connect GPT-4, Claude, Gemini, or open-weight models into production pipelines with structured outputs and fallback logic.
Voice Agent Development
Real-time voice pipelines with VAD, STT, TTS, and LLM orchestration for phone, IVR, and conversational interfaces.
Multi-agent Orchestration
Coordinate fleets of specialized agents with shared memory, tool calls, and human-in-the-loop checkpoints.
RAG & Knowledge Systems
Retrieval-augmented generation with vector databases, hybrid search, and contextual grounding for accurate, cite-able answers.
Agent Observability
Full tracing, evaluation, and monitoring so every agent decision is reproducible and debuggable in production.
Production Hardening
Rate limiting, fallbacks, cost controls, and zero-data-retention LLM configurations for regulated environments.
Where teams apply AI Agents
These are the problems we most commonly solve. Every engagement starts with your specific context, not a template.
Clinic front-desk calling and appointment booking automation
E-commerce catalog management and customer support agents
Document processing and structured data extraction pipelines
Internal knowledge assistants for enterprise teams
Technologies and tools
Selected to fit the problem, not the trend.
Other practice areas
Let's talk about AI Agents
Tell us what you are building and where you are stuck. We will respond with honest scoping.