DIGITAL KITCHEN
AGENTIC AI

Agentic AI Development. Multi-Agent Systems Built for Production.

Agents that reason, plan, and act across your tools. With orchestration, fallbacks, and observability you can actually run.

Agentic AI development means building systems where multiple AI agents collaborate to handle workflows no single chatbot can. We design the agent graph, pick the orchestration layer, wire in tool use and memory, and ship something you can monitor in production. Most builds run on Claude or GPT-4 with LangGraph or a custom orchestrator.

By Gianluca Boccadifuoco

WHAT YOU GET

Everything in the box.

Multi-agent architecture

A graph of specialised agents, not one monolithic prompt. Each agent does one thing well.

Orchestration layer

LangGraph, CrewAI, or a custom orchestrator depending on your needs. We pick what fits, not what we like.

Tool use + memory

Function calling, short-term and long-term memory, retrieval where it earns its keep.

Observability

Every step logged. LangSmith or Helicone integration. So you know why an agent picked a path.

Fallback handling

When an agent goes off the rails, it doesn't take the user with it. Graceful degradation by default.

Prompt versioning

Prompts as code. Change history. Rollback. So tuning a prompt in week 12 doesn't break what worked in week 4.

THE PROCESS

How we build it.

1

Map workflow

We map the human workflow first. Where do decisions happen? What can be automated, what should not be.

2

Design graph

Agent roles, tool permissions, escalation paths. The architecture before the code.

3

Build

3 to 5 weeks. Iterate on real data, not synthetic prompts. Demo weekly.

4

Tune in prod

Two weeks of tuning against real traffic. Then handover.

STACK

Tools we use.

Claude (Anthropic)GPT-4o (OpenAI)LangGraphCrewAILangSmithHeliconePineconeWeaviateCustom orchestrators
PRICING

Fixed-price projects.

Discovery scoping is free. Most agentic builds land between $25,000 and $80,000 depending on agent count, integrations, and observability needs. Custom retainers for ongoing tuning and feature development.

If your scope can fit in a single-agent build, we tell you. We don't sell complexity for its own sake.

FAQ

Common questions.

Agentic AI is software that uses LLMs to plan, decide, and act over multiple steps, often using tools to interact with other software. The difference from a chatbot: a chatbot answers questions, an agentic system completes tasks.
Yes, with caveats. The current generation of frontier models (Claude 3.7+, GPT-4o, GPT-4.1) is reliable enough for production agents on well-scoped tasks. The risk isn't model quality, it's scope. Agents that try to do too much fail unpredictably.
LangSmith for trace logging, Helicone for cost monitoring, custom dashboards for business metrics. Every prompt, every tool call, every fallback gets logged. You see what the agent did and why.
Token costs scale with traffic. A typical mid-volume agent costs $200 to $2,000 per month in API spend, depending on traffic and model choice. We optimize for cost during build, not as an afterthought.
4 to 8 weeks for most builds. Single-agent task automation lands at 4 weeks. Multi-agent systems with several integrations and a custom UI take closer to 8. We tell you which side you fall on during the free scoping call.
FREE SCOPING CALL

Got a workflow that needs an agent system?

30 minutes. We map the workflow and tell you whether agentic is the right answer.

RELATED READING

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When to build which. With a decision matrix.

AI Agent Development

Single-agent builds and the broader service.

LangChain Alternatives

7 LLM orchestration tools we evaluated.