AI Agent DevelopmentThat Ships to Production
We design, build, and operate autonomous AI agents for support, sales, voice, documents, and operations — grounded in your data, guarded by human-in-the-loop controls, and integrated with the systems you already run. Fixed-scope quotes within 48 hours.
What are AI agent development services?
AI agent development services cover the design, build, and deployment of autonomous LLM-powered agents that complete business tasks — support resolution, sales outreach, voice calls, document processing, and workflow orchestration. AgileSoftLabs builds production agents on LangChain, CrewAI, the OpenAI Agents SDK, and MCP, with RAG grounding, guardrails, and human-in-the-loop controls. Builds start at $3,600 with fixed-scope quotes in 48 hours.
- Starting price
- From $3,600
- Typical delivery
- 4–12 weeks
- Frameworks
- LangChain, CrewAI, Agents SDK, MCP
- Track record
- 200+ AI projects, 12+ years
Last verified: July 2026
AI Agents We Build
Every agent type below is backed by a deployed product you can evaluate — not a slide deck.
Customer Support Agents
Autonomous agents that resolve tickets, answer product questions from your knowledge base (RAG), and escalate to humans with full context when needed.
See Business AI OS →AI Voice Agents
Natural-language phone agents for appointment booking, qualification calls, and 24/7 support — with compliance guardrails and call analytics.
See AI Voice Agent →AI Sales Agents (SDR)
Autonomous lead qualification, personalized outbound, and meeting scheduling that plugs into your existing CRM.
See AI Sales Agent →Document Processing Agents
Contract analysis, invoice extraction, and compliance review with human-in-the-loop verification for high-stakes documents.
See AI Document Processing →Workflow & Operations Agents
Multi-agent orchestration that automates cross-system business processes — approvals, reporting, reconciliation — with audit trails.
See AI Workflow Automation →Custom & Industry Agents
Purpose-built agents for healthcare scheduling, fintech operations, manufacturing procurement, and other regulated, domain-specific workflows.
Explore all AI agent products →Frameworks & Stack We Work With
We publish what we learn — each stack choice links to our production write-up.
LangChain & LangGraph
Agent orchestration, tool calling, and stateful graphs for complex flows
LangChain vs CrewAI vs AutoGen — our production verdict →CrewAI
Role-based multi-agent crews — fastest path to structured agent teams
CrewAI in production: real lessons →Model Context Protocol (MCP)
Standardized tool access so agents work across vendors and stay portable
How AI agents use MCP →RAG & Agent Memory
Vector stores, long-term memory, and retrieval pipelines that keep agents grounded
Long-term agent memory with LangChain →AWS Bedrock / Azure OpenAI / Vertex AI
Enterprise LLM platform selection for compliance, latency, and cost
Bedrock vs Azure OpenAI vs Vertex — 2026 comparison →How We Deliver Production Agents
1. Scope
Use-case selection, ROI model, and data audit. Fixed quote within 48 hours.
2. Design
Framework and model selection, tool/API inventory, guardrail and escalation design.
3. Build
Agent + integrations + RAG grounding, with evaluation suites run on every change.
4. Operate
Staged rollout with human-in-the-loop, monitoring, cost optimization, and tuning.
Production AI, With Published Results
Guidehouse — AI Billing Automation
85% processing-time reduction, $2.5M saved, 99.2% accuracy in healthcare billing.
Read the case study →Gaston AI — Hospitality Platform
200+ hotels served, 1M+ guest interactions, 96% satisfaction.
Read the case study →DX4 — API Automation
85% time reduction and $25K+ savings per generation cycle.
Read the case study →Our AI Agent Engineering Guides
The research behind our builds — read before you buy, from anyone.
AI Agent Development: Frequently Asked Questions
What does an AI agent development company do?
An AI agent development company designs, builds, and deploys autonomous software agents that complete business tasks — answering support tickets, qualifying leads, processing documents, or orchestrating workflows — using large language models with tool access, memory, and guardrails. AgileSoftLabs handles the full lifecycle: use-case scoping, framework selection, integration with your systems, safety controls, and post-launch monitoring.
How much does AI agent development cost?
AgileSoftLabs enterprise AI agent builds start at $3,600, with most production deployments scoped as fixed-price projects after a free consultation. Ongoing costs are primarily LLM usage fees, which we optimize through model routing and caching. Use our AI agent pricing calculator for an instant estimate on your use case.
Which framework is best — LangChain, CrewAI, or AutoGen?
It depends on the workload: LangChain/LangGraph suits complex stateful workflows with many tools, CrewAI is fastest for role-based agent teams, and AutoGen fits research-style multi-agent conversation. We have shipped production systems on all three and select per project — our published comparison covers cost, latency, and maintainability trade-offs.
How long does it take to build a production AI agent?
A scoped single-purpose agent (support, scheduling, document processing) typically ships in 4–8 weeks including integration and guardrail testing. Multi-agent systems with several integrations usually take 8–12 weeks. AgileSoftLabs delivers most fixed-scope builds inside 60–90 days.
How do you keep AI agents safe and accurate?
Every deployment includes guardrails (input/output filtering, allowed-action scoping), human-in-the-loop approval for high-stakes actions, RAG grounding against your verified data to reduce hallucination, full audit logging, and evaluation suites run before and after each change.
Can AI agents integrate with our existing systems?
Yes — that is most of the work. We integrate agents with CRMs, ERPs, help desks, EHRs, and internal APIs, increasingly through the Model Context Protocol (MCP) so tool integrations stay portable across LLM vendors.
Do you build with OpenAI, Claude, or open-source models?
All of the above. We select models per task and deploy on AWS Bedrock, Azure OpenAI, or Google Vertex AI when enterprise compliance requires it, and use open-weight models where data residency or cost demands. Architectures are model-agnostic so you are not locked to one vendor.
What proof do you have that your AI systems work in production?
Published case studies include AI billing automation for Guidehouse (85% processing-time reduction, $2.5M saved, 99.2% accuracy), the Gaston AI hospitality platform (200+ hotels, 1M+ interactions, 96% satisfaction), and DX4 API automation (85% time reduction). AgileSoftLabs has delivered 200+ outcomes over 12+ years.
Ship Your First Production Agent This Quarter
Free consultation, fixed-scope quote in 48 hours, delivery in 60–90 days.
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