Agentic AI
Build MCP servers, agents, and automation workflows for business. Connect tools, documents, APIs, and processes into intelligent systems that execute tasks autonomously.
What we do
Agentic AI goes beyond chatbots. We build autonomous systems that can use tools, access documents, call APIs, make decisions, and execute multi-step workflows. Using MCP (Model Context Protocol) and modern agent frameworks, we create AI systems that integrate directly into your business operations - with proper observability, testing, and human-in-the-loop controls.
MCP Servers
Build Model Context Protocol servers that connect LLMs to your tools, databases, and business systems in a standardized way.
Business Automation
Automate complex multi-step workflows: document processing, data entry, email handling, report generation, and task routing.
RAG Systems
Retrieval-Augmented Generation: connect LLMs to your documents, knowledge bases, and databases for accurate, grounded responses.
Workflow Agents
Agents that execute multi-step tasks: research, data analysis, report writing, customer support, and internal operations.
Tool-Use Agents
AI agents that can call APIs, run code, query databases, and interact with external systems to complete tasks.
Human-in-the-Loop
Design agents with proper oversight: approval gates, escalation paths, and audit trails for sensitive decisions.
What you need to get started
Workflow to automate
A clear business process that involves multiple steps, decisions, or tool interactions. The more repetitive and rule-based, the better.
Tools and systems to connect
APIs, databases, document stores, or internal tools the agent needs to interact with. Access credentials and documentation help.
Decision boundaries
What can the agent decide autonomously? What requires human approval? Define the guardrails clearly.
Success metrics
How will you measure the agent's performance? Accuracy, speed, cost savings, or user satisfaction?
What we've built
ATLAS Benchmark - Agent Evaluation
Built an AI evaluation system that tests how agents learn through interactive tasks. Includes replay viewer, adaptation testing, and failure mode analysis across multiple learning faculties: associative learning, concept formation, probabilistic learning, procedural learning, language learning, and observational learning.
Ready to build an AI agent?
Tell us about the workflow you want to automate.