→ AI agent development services
AI agent development services for agents that survive production
Multi-step agents that take actions, not just generate text. Built on LangGraph or Agno. Tool calls, state, recovery plans, eval coverage. Integrated with your existing systems.
Overview
How we approach this work.
AI agent development services from Resser cover production-grade agents: agents that read from your real data, write to your real systems, and survive contact with real traffic.
We build on LangGraph for stateful multi-step agents and Agno for lighter orchestration. We have shipped agents for compliance review, sales operations, knowledge retrieval, and internal copilots embedded in existing software.
Every agent we ship has an eval suite, structured tool definitions, retry logic, cost ceilings, and an audit log. Without those, an agent is a science project. With them, it is a production feature.
What we build
Concrete deliverables.
Multi-step reasoning agents
LangGraph state machines with branching, retries, human checkpoints, and recovery plans.
Tool-using agents
Agents that call your real APIs, query your real database, and write to your real CRM with structured schemas and dry-run modes.
Knowledge-base RAG agents
Agents that search across SharePoint, Confluence, Notion, internal docs, and cite their sources or escalate.
Compliance and review agents
Human-in-the-loop agents that prepare decisions for human review with full citation and audit trail.
Operations copilots
Internal-facing agents that help your ops team handle non-routine cases faster.
Multi-agent orchestration
When the problem benefits from specialist agents (researcher, planner, executor, critic) coordinated by a supervisor.
Stack
What we build with.
Frameworks
LangGraph for stateful agents. Agno for lightweight orchestration. Vercel AI SDK for streaming agent UIs. Pydantic AI for typed Python agents.
Models
Anthropic Claude Sonnet and Opus for reasoning-heavy agents. GPT-4o for structured extraction. Open-weights (Llama, Qwen) when sovereignty demands it.
Eval and observability
LangSmith for hosted agent traces. Braintrust for CI-driven eval. Helicone for cost. Custom eval harnesses per agent.
State and persistence
Postgres for agent state and audit log. Redis for short-lived state. S3 for artifacts. Temporal when durable execution is the constraint.
Outcomes
What we ship.
Compliance review agent: reviewer time-per-case dramatically reduced; human-in-the-loop kept authority on every decision.
Knowledge-base agent: minutes of search collapsed to seconds, every answer cited from the source with refusal when no source meets the threshold.
Healthcare triage agent: meaningful accuracy lift over the manual baseline with materially lower per-case cost.
References with names available after a scoping call.
Related services
Other places this work shows up.
FAQ
Frequently asked.
What is the difference between an AI agent and a chatbot?
A chatbot generates text in response to a message. An AI agent takes actions: it queries APIs, writes to databases, calls tools, runs multi-step workflows, and recovers when steps fail. We build agents, not chatbots.
LangGraph vs Agno vs roll-your-own?
LangGraph for stateful multi-step agents with branching and human checkpoints. Agno for simpler orchestration where the overhead of LangGraph is not worth it. Roll-your-own when the agent shape is unusual enough that frameworks add more friction than value. We pick based on your scope in discovery week.
Can the agent integrate with our CRM, ERP, internal database?
Yes. Tool definitions point to your real APIs with strict schemas, dry-run modes, and audit logging. We have integrated agents with Salesforce, SAP, Dynamics, NetSuite, internal Postgres and SQL Server.
How much does an AI agent build cost?
A single-purpose agent integrated with one system: €15,000-€40,000. A multi-step agent across 2-3 systems with audit and eval: €40,000-€100,000. Multi-agent orchestration with admin tooling: €100,000+.
Want to scope this for your project?
Fill the project-estimate form. We reply within one business day with a preliminary scope and a rough budget bracket.