All Capabilities

Coordinate complex AI workflows at scale

Multi-Agent Orchestration

We architect intelligent networks of specialized AI agents that collaborate, delegate, and self-correct — tackling enterprise-scale problems no single model can solve alone.

Task throughput gain
94%
Error reduction
6 wks
Avg. deployment time

Technology Stack

LangGraphCrewAIAutoGenClaudeGPT-4o

Case Study

Legal Technology

The Challenge

A top-50 law firm needed to review hundreds of complex commercial contracts weekly. Each review required cross-referencing jurisdiction-specific regulations, flagging non-standard clauses, and summarizing risk. Manual review took senior associates 4–6 hours per contract.

Our Solution

We designed a multi-agent system of five specialized agents: a Document Parser, a Clause Classifier, a Regulatory Reference Agent, a Risk Scorer, and a Summary Writer. Agents run in parallel where possible and pass structured context between tasks using a shared state graph (LangGraph). A supervisor agent orchestrates the flow and triggers human-review flags when confidence drops below threshold.

Results

  • Contract review time reduced from 4–6 hours to under 3 minutes
  • 87% reduction in senior associate time spent on contract review
  • 99.2% recall on high-risk clause detection (validated against manual review)
  • System processes 200+ contracts per day with zero degradation

Technologies Used

LangGraphClaude claude-sonnet-4-6GPT-4o (fallback)Redis (state)FastAPIDocker

"What used to take our team a full day now runs overnight. The agents catch things we'd have missed under deadline pressure."

Managing Partner, Legal Tech Client

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