Production-Ready MVPs
Web Platforms
Internal Tools
Clean Architecture
Fast Execution
Clear Ownership
Product Scaling
Dashboards & Ops
Reliable Delivery
Senior Engineers
Pragmatic AI
Business Impact
Production-Ready MVPs
Web Platforms
Internal Tools
Clean Architecture
Fast Execution
Clear Ownership
Product Scaling
Dashboards & Ops
Reliable Delivery
Senior Engineers
Pragmatic AI
Business Impact
LLM Agents & Automation
Automate your workflows, customer support, and internal ops with powerful AI agents that think, act, and iterate. We help you build real-time, multi-step agents powered by GPT, Claude, and open-source LLMs.
Using frameworks like LangChain, AutoGen, and ReAct, we create agents that can retrieve, reason, and execute — integrated with tools like Zapier, Notion, Google Docs, and APIs tailored to your business.
Service Overview
LLM agents bring decision-making and automation together. We design task-driven, multi-agent systems that can search documents, write summaries, trigger actions, and respond in real-time — all while managing context, memory, and logic flow.
Think of it as your next-gen digital teammate — trained to do repetitive work so your team can scale faster.
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Years of experience this field
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Number of projects completed
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Number of awards achieved
Key Features
Our agent architectures are composable, extendable, and tool-aware — built for real business use.
- Custom LLM Agents (LangChain, AutoGen, crewAI)
- Multi-Step Reasoning & Tool Usage (ReAct, MRKL)
- API Integrations (Zapier, Slack, Notion, Stripe)
- Memory, Embeddings & Vector Search (Pinecone, Chroma)
- Hosted or Self-Hosted Agent Workflows (Docker, Vercel, Airflow)
LLM agents are autonomous or semi-autonomous AI programs powered by language models. They can execute tasks, make decisions, call APIs, search knowledge bases, and automate business workflows like content creation, support, and reporting.
We use LangChain, AutoGen, crewAI, OpenAI function-calling, ReAct, MRKL, and embeddings-based memory with vector DBs like Pinecone or Chroma. Integrations include APIs, CRMs, databases, and SaaS tools.
Yes. Agents can be connected to Slack, Notion, Zapier, Stripe, CRMs, email platforms, and custom APIs. We make them context-aware with secure memory and logging.
Both. We can deploy agents via Vercel, Render, AWS Lambda, or on your own cloud using Docker, Airflow, or serverless runtimes — with observability and rate limiting.
Unlike static chatbots, LLM agents can plan steps, access tools, remember past interactions, and work in sequences. They’re more autonomous, stateful, and capable of completing multi-step tasks.