Solution // agentic systems
Agentic Systems & AI Integration
Stateful multi-agent workflows, tool-calling with ADK and Microsoft Foundry, advanced RAG, private edge AI, and domain fine-tuning (LoRA).
What it is
Designing, building, and deploying production-grade AI systems that execute real work. Rather than fragile prompt chains or generic chat interfaces, we engineer deterministic multi-agent state machines, hybrid retrieval pipelines (RAG), private on-premise/edge inferencing, and parameter-efficient domain fine-tuning (LoRA / QLoRA) wrapped in verifiable evaluation benchmarks.
What you get
- Stateful multi-agent pipelines: Cyclic execution graphs, schema validation, and human-in-the-loop approvals using LangGraph or Agno
- Enterprise model orchestration: Tool-calling and agent coordination via Google ADK and Microsoft AI Foundry
- Advanced RAG architecture: Hybrid semantic search, vector storage (pgvector), and contextual chunking over your private data
- Edge AI & On-Premise deployments: Local inference behind strict firewalls and on private VPCs for zero data leakage
- Domain Fine-Tuning: Parameter-efficient adaptation (LoRA / QLoRA) on your internal domain corpora
- Guardrails & Evaluation: Precision benchmarks against your labelled data, confidence thresholds, refusal handling, and OpenTelemetry observability
- Full ownership: Infrastructure-as-code and running source repositories transferred to your organization on day one
What it runs on
LangGraph · Agno · Google ADK · Microsoft AI Foundry · Python / FastAPI · pgvector / PostgreSQL · Docker · Cloudflare Workers · OpenTelemetry tracing.
Timeline and price
- 2-Week Tactical Sprint: Focused implementation of a specific multi-agent workflow or RAG pipeline.
- 4–6 Week Production Integration: End-to-end multi-agent orchestration, fine-tuning or evaluation pipeline.
- Fixed price quoted before work begins. Cloud and token costs bill direct to your accounts at cost.