Deploy Intelligent AI Agents That Work For You 24/7

Unlike standard chatbots that only respond to text, our AI agents run autonomously. Powered by models like GPT-4o and Claude 3.5 Sonnet, they execute multi-step workflows, query database records, and call external APIs. Built using LangChain and CrewAI, they continuously monitor outcomes to handle failures without manual intervention.

A standard AI agent deployment takes 7 to 11 weeks following our four-phase engineering pipeline. This includes 1 to 2 weeks for scoping, 3 to 4 weeks for logic development, 2 to 3 weeks for sandbox security testing, and 1 to 2 weeks for production deployment. We deliver functional prototypes at the end of each phase.

Our agents automate data workflows like database syncs, multi-step API orchestration, and document extraction. We also deploy specialized support desk agents that connect to ticketing APIs and developer assistants for automated pull request checks. If a workflow has defined API endpoints and routing rules, an agent can run it.

We build custom connectors for REST and GraphQL APIs, SQL databases, and message brokers like Slack. Our engineers use LangChain and LlamaIndex to query internal databases without modifying your existing software architecture. All integration pipelines run on secure AWS cloud infrastructure with strict IAM security boundaries.

We track agent execution logs to identify edge cases, API timeouts, and low-confidence decisions. Using this interaction data, we refine prompt templates and system instructions in monthly optimization sprints. When necessary, we compile these logs to fine-tune your proprietary LLM models on AWS or OpenAI.

Our custom AI agent projects start at $25,000 for single-task automations and scale to $60,000+ for multi-agent systems, delivering half the cost of traditional agencies. Every project includes complete code ownership and a 30-day post-launch support period at no extra charge. We estimate API token usage early to ensure predictable monthly costs.

We integrate real-time token spend tracking and hard monthly budget caps for every agent. If an agent encounters a repetitive execution loop, our system automatically pauses the run and alerts engineers via Slack before exceeding cost limits.

Our agents are built with automated retry logic, exponential backoff, and fallback LLM routing to Gemini or Anthropic if the primary OpenAI model is down. This ensures near-zero downtime and continuous workflow execution even during provider outages.