Autonomous AI Agents & Multi Agent Systems

Chatbots just talk. Agents do work. We build deterministic, enterprise-grade Multi-Agent Systems that plan workflows, call tools (APIs/ERPs), and collaborate to execute complex business operations—autonomously and securely.

The Difference Between a Copilot and an Agent

Planning & Reasoning

Agents don't just answer; they plan. They break complex goals (e.g., "Onboard Client") into sequential steps and execute them one by one.

Tool Execution

Agents are authorized to use tools. They can look up data in Salesforce, send emails via Gmail, and create tickets in Jira via API.

Collaboration

We deploy "Swarms" where specialized agents (e.g., a Researcher and a Writer) hand off tasks to each other to complete a complex job.

Your New Digital Workforce

Orchestrator (Supervisor) Agents

Analyzes user requests and delegates tasks to sub-agents. Maintains the state of the workflow and ensures completion.

Research & Analysis Agents

Browses the web or RAG systems to gather information. Synthesizes data into structured reports (e.g., Competitor Analysis).

Operational/Transactional Agents

Executes API calls: Creating CRM records, processing refunds, or scheduling meetings. Works with strictly defined API schemas.

Document Processing Agents

Extracts specific fields from documents. Validates accuracy against database records.

Coding & Data Agents

Writes and executes Python/SQL code to analyze datasets. Generates charts and debugs error logs autonomously.

Compliance & Safety Agents

Reviews the output of other agents before it reaches the user. Checks for PII leaks, hallucination, or policy violations.

Built on Cutting Edge Frameworks

We engineer robust state machines, not fragile scripts.

Orchestration

LangGraph

LangGraph

CrewAI

CrewAI

Microsoft AutoGen

OpenAI Swarm

LLM Brains

GPT-4o

Claude 3.5 Sonnet

Claude 3.5 Sonnet

Llama 3

Llama 3

Tooling

LangChain Tools

Slack SDK

Zapier NLA

Memory

MemGPT

Redis

Redis

Pinecone

Pinecone

The "Supervisor-Worker" Architecture

How multiple agents collaborate to solve complex problems without getting stuck.
Diagram of Multi-Agent System.

Agents in Production: Real Results

KYC & Onboarding Swarm

A "Document Agent" extracts ID data, a "Risk Agent" checks sanctions, and a "Communication Agent" emails the client. Reduced onboarding time by 80%.

Logistics Exception Handler

An autonomous agent monitors shipment delays, re-calculates routes via API, and notifies vendors automatically.

L2 Technical Support Agent

An agent that reads logs, queries the code repo, suggests a fix, and drafts the reply for a human engineer to approve.

Solutions Powered by Agents

We deploy agentic workflows to solve these specific business problems.

Engineering & Safety Questions

We implement “Human-in-the-Loop” checkpoints. For critical actions (like sending money or deleting files), the Agent must pause and request human approval via Slack or Email before proceeding.

Yes. We use standard Function Calling (OpenAI/Anthropic) to connect agents to your APIs. We can also build custom MCP (Model Context Protocol) servers for secure integration.

We use State Machines (LangGraph) rather than open-ended loops. Every agent has a maximum number of steps (e.g., 5 attempts) before it must abort and alert a human supervisor.

Delivering AI Solutions Across the Globe

Ready to Hire Your Digital Workforce?

Move from manual workflows to autonomous execution.

Scroll to Top