Autonomous AI Agents That Get Work Done
We build AI agents that plan, reason, and execute complex multi-step workflows autonomously ā single agents, multi-agent systems, and full agentic pipelines using LangGraph, CrewAI, and AutoGen.
What We Build for AI Agent Deployments
Six core capabilities delivered in every agentic system we architect and deploy.
Autonomous Agents
Goal-driven agents that decompose complex objectives into subtasks, plan execution paths, and adapt when steps fail ā without human intervention at each step.
Multi-Agent Systems
Collaborative agent networks where specialized agents ā researcher, planner, executor, critic ā work in parallel or in sequence using CrewAI and LangGraph orchestration.
Agent Workflows
Structured agentic pipelines with conditional logic, retry mechanisms, human-in-the-loop checkpoints, and event-driven triggers for end-to-end process automation.
Tool Integrations
Agents equipped with 50+ tool integrations ā web search, code execution, CRM write-back, email dispatch, database queries, and custom internal API calls.
Agent Memory & Context
Long-term memory with Pinecone or Weaviate vector stores, short-term episodic buffers, and shared memory across multi-agent sessions for stateful execution.
Agent Monitoring
Full observability dashboards with step-level traces, token usage, tool call logs, error rates, and goal completion metrics ā LangSmith and custom tooling.
How We Build Your AI Agents
From discovery to production-ready deployment in 6 weeks.
Discovery & Architecture
We map your target workflows, define agent roles and responsibilities, select the right orchestration framework (LangGraph for stateful workflows, CrewAI for role-based systems), and design the agent graph before any code is written.
Agent Design & Prompt Engineering
Each agent receives a precisely engineered system prompt defining its persona, available tools, decision boundaries, and escalation criteria. We run adversarial testing to harden agent behavior.
Tool Integration
We build the tool layer ā custom functions, API wrappers, and MCP-compatible tool definitions that agents can call reliably. Every tool gets input validation, error handling, and retry logic.
Testing & Evaluation
Agents are stress-tested on 100+ real task scenarios including edge cases and adversarial inputs. We measure goal completion rate, hallucination rate, and average steps-to-completion.
Deployment & Monitoring
Production deployment on your infrastructure (AWS, GCP, Azure, or on-premises) with LangSmith tracing, alerting, and a 30-day hypercare period post-launch.
Technology Stack
AI Agents Across Industries
We build domain-specific agents trained on industry workflows, terminology, and compliance requirements.
Insurance
Automated claims investigation, policy renewal agents, underwriting data collection
Healthcare
Prior authorization agents, patient intake automation, clinical document processing
Legal
Contract review agents, due diligence automation, legal research and citation agents
SaaS
Autonomous onboarding agents, technical support agents, usage-based billing analysis
E-commerce
Product sourcing agents, pricing intelligence, order exception handling
Finance
Transaction monitoring agents, compliance reporting, financial data extraction
HR & Recruitment
CV screening agents, interview scheduling, onboarding workflow orchestration
Why Teams Choose Infonza for AI Agents
Agentic-First Team
Our engineers specialize in agentic systems ā not LLM wrappers. We've built multi-agent pipelines in LangGraph, CrewAI, and AutoGen across production environments.
Tool & Integration Depth
We build robust tool layers ā not just sample code. Every tool integration includes error handling, retries, input sanitization, and observability hooks.
Evaluation-Driven Development
Every agent is evaluated against a benchmark task suite before release. We track goal completion rate, hallucination rate, and wall-clock time per workflow.
Production-Ready Architecture
Agents deployed to real infrastructure with monitoring, alerting, horizontal scaling, and graceful degradation ā not just a Jupyter notebook demo.
Post-Launch Partnership
30-day hypercare with weekly agent performance reviews. We tune prompts, fix tool failures, and expand capabilities based on live data from your first month.
Ready to deploy your first AI agent?
Get a free architecture review of your target workflow from a senior AI engineer.
Related Services
Frequently Asked Questions
Honest answers to technical questions about AI agents development.
Ready to Deploy Your First AI Agent?
Schedule a 30-minute session with our AI agents engineers. We'll review your target workflow, recommend the right orchestration framework, and give you a realistic scope before you commit.