Autonomous AI Agents

AI Agents That Do the Work

AI agent development at Agility produces autonomous multi-step systems that plan, use tools, and execute workflows without human input. Built on LangGraph, AutoGen, and custom orchestration layers using GPT-4o and Claude 3.5, these agents handle tasks like researching and drafting reports end-to-end, processing and routing support tickets, enriching CRM records from web sources, generating and validating code, and executing data pipelines with full exception handling. Each agent connects to your existing tools — APIs, databases, browsers, file systems — through tested integrations, not brittle screen automations. Deployment runs 3–6 weeks from scoping to production. We deliver the agent system, an evaluation framework measuring task completion rate and error rate, monitoring dashboards, and runbooks for your engineering team. Every execution is logged, exceptions are flagged for human review, and all failure modes are mapped before go-live.

3–6
Weeks to Prod
90%+
Task Automation Rate
200+
AI Projects Shipped
0
Human Steps Required

Agents for Every Function

We build agents that slot into your business workflows and execute tasks that used to require human staff

Research & Analysis Agents

Agents that browse the web, pull from databases, synthesise reports, and surface insights autonomously

  • Competitive intelligence
  • Market research
  • Due diligence reports
  • News monitoring & summaries

Sales & Outreach Agents

Fully autonomous prospecting — find leads, enrich data, personalise outreach, and log to CRM without human input

  • Lead discovery & enrichment
  • Personalised email sequences
  • LinkedIn outreach
  • Follow-up automation

Data Processing Agents

End-to-end data pipelines where the agent reads, transforms, validates, and writes data across systems

  • Invoice & document extraction
  • ERP data sync
  • Data quality checks
  • Automated reporting

Multi-Agent Orchestration

Architect systems where multiple specialised agents collaborate — planner, executor, verifier — to handle complex workflows

  • LangGraph agent networks
  • Tool-calling pipelines
  • Human-in-the-loop approval
  • Parallel task execution

Engineering & DevOps Agents

Agents that write code, run tests, fix bugs, and open PRs — accelerating your engineering velocity

  • Code generation & review
  • Test generation
  • Infrastructure provisioning
  • Incident triage

Customer-Facing Agents

Conversational agents with memory, tool use, and the ability to take real actions inside your systems

  • Order management
  • Account self-service
  • Booking & scheduling
  • Returns & complaints

How We Build Your Agent

01

Agent Design Workshop

Map the exact workflow, define tool access, guardrails, and success metrics for your agent

3–5 days
02

Tool & Integration Build

Build every tool the agent needs — APIs, DB connections, web scraping, file I/O, external services

1–2 weeks
03

Agent Development & Evals

Build the agent loop, test against real scenarios, tune prompts and routing logic, measure reliability

2–4 weeks
04

Deploy & Monitor

Production deployment with observability, failure alerting, and human escalation paths

1 week

Agent Tech Stack

Agent Frameworks

LangGraphLangChain AgentsAutoGenCrewAICustom loops

LLMs

GPT-4oClaude Opus / SonnetGemini ProLlama 3.1Mistral Large

Tool Calling

OpenAI Function CallingClaude Tool UseMCP (Model Context Protocol)

Memory & RAG

PineconeWeaviatepgvectorRedisChroma

Orchestration

KubernetesCeleryTemporalAWS Step FunctionsDocker

Observability

LangSmithWeights & BiasesHeliconeCustom dashboards

AI Agent Development: Common Questions

What teams ask before commissioning an autonomous AI agent.

AI agent development is building autonomous software that plans and executes multi-step tasks on its own — using tools, APIs, and data — instead of just answering a single prompt. Agility builds these agents on frameworks like LangGraph and AutoGen with GPT-4o and Claude, so they can research, decide, act, and handle exceptions across a full workflow.

Agents handle multi-step knowledge work: researching a topic and drafting a report end to end, triaging and routing support tickets, enriching CRM records from web sources, generating and validating code, and running data pipelines with exception handling. If a workflow has clear steps and connects to tools or APIs, an agent can usually automate it.

We deliver production agents in 3-6 weeks from scoping to deployment, with a working prototype often ready in under two weeks. Timeline depends on how many tools the agent integrates with and how much evaluation and guardrail work the use case requires.

Most agent projects range from $20,000 to $120,000 depending on the number of integrations, the complexity of the workflow, and the evaluation and monitoring required. We scope each build to a fixed price with milestones before development starts. Book a free scoping call for a concrete estimate.

Every agent ships with an evaluation framework measuring task-completion and error rates, full execution logging, human-in-the-loop review on flagged actions, and mapped failure modes before go-live. We use tested API and database integrations rather than brittle screen automation, and add guardrails so agents fail safely instead of acting on bad data.

Agents connect to your existing tools — APIs, databases, browsers, and file systems — through tested integrations, and run inside your environment so your data stays under your control. You receive the deployed agent system, the evaluation harness, monitoring dashboards, and runbooks for your engineering team.

Build an Agent That Works While You Sleep

Tell us the workflow you want to automate. We'll scope it and have a working agent prototype in under two weeks.