LangChain
- Custom tool & function integration
- Memory & conversation state
- Multi-agent orchestration
Agent & RAG Orchestration
LangChain & LlamaIndex Orchestration
Retrieval-augmented and multi-step agent systems built on proven orchestration frameworks.
Why Retrieval & Orchestration Matter
Models can't answer questions about your private or recent data out of the box, and a single prompt-response can't handle multi-step tasks that need tools or memory. Grounding answers in retrieved documents and orchestrating multi-step agent workflows turns a chatbot into a system that can actually get work done.
The Business Impact
- Grounded Answers
Responses traceable back to your actual documents and data.
- Multi-Step Automation
Agents handle full workflows, not just single Q&A turns.
- Reduced Hallucinations
Retrieval grounding and evaluation gates cut ungrounded answers.
Where We Work
From retrieval pipelines to fully orchestrated agents.
LlamaIndex
- Document ingestion & chunking
- Hybrid search (semantic + keyword)
- Structured & unstructured queries
Evaluation & Guardrails
- Retrieval relevance evaluation
- Hallucination detection
- Human-in-the-loop approval
How We Help
From a retrieval pipeline to a fully orchestrated agent system.
RAG Pipeline Development
Ground answers in your dataWe build ingestion, chunking, and retrieval pipelines so answers are grounded in your actual documents.
90%+
Answer Grounding
- Document ingestion & chunking strategy
- Hybrid semantic + keyword search
- Query engines over your data
Agent Orchestration
Multi-step, not single-shotAgents that plan, call tools, and self-correct — with approval gates wherever the action is consequential.
70%
Workflows with HITL Gates
- Multi-agent orchestration
- Tool & API integration
- Human-in-the-loop checkpoints
What This Looks Like in Practice
Results teams see after grounding their AI in real data.
90%+
Answer grounding
Target rate of responses traceable back to a retrieved source document.
Multi-step
Task automation
Agents handle multi-step workflows, not just single Q&A turns.
Reduced
Hallucination rate
Retrieval grounding and evaluation gates measurably cut ungrounded answers.
Why Teams Choose Us
Grounded, evaluated agent systems, not a demo prompt chain.
Grounded by Default
Every answer traces back to a retrieved source, not just model memory.
- Hybrid semantic + keyword retrieval
- 90%+ grounding target
Human-in-the-Loop Where It Counts
Approval gates before any irreversible or high-cost action an agent takes.
- Configurable approval checkpoints
- Audit trail on every tool call
Evaluated, Not Just Shipped
Continuous evaluation pipelines catch regressions before users do.
- Automated relevance evaluation
- Hallucination detection gates
Frequently Asked Questions
Common questions about our Agent & RAG Orchestration and implementation services.