AI & Automation

Hire an AI chatbot developer who ships to production

Custom LLM chatbots, retrieval-augmented (RAG) assistants and tool-using AI agents, engineered with evaluation, security and cost control from day one, not bolted together from a template.

RAGTool callingEvalsCustom UI

The short version

When a no-code chatbot builder isn’t enough

Chatbot builders are great for simple FAQ bots. You need a developer when the bot must search thousands of documents accurately, call your internal APIs, respect user permissions, run inside your product, or meet security requirements.

Our developers work in TypeScript and Python, use proven frameworks where they help and plain code where they don’t, and ship with automated evaluations so you can measure accuracy before and after every change.

What's included

  • Architecture and model selection
  • RAG pipeline: ingestion, chunking, embeddings, retrieval
  • Tool / function calling to your APIs
  • Custom chat UI or embedding in your app
  • Evaluation suite and guardrails
  • Deployment, monitoring and documentation
Get a fixed-price scope

Capabilities

What you get with AI Chatbot Developer

RAG done properly

Hybrid search, reranking and citations so answers are grounded and verifiable.

Tool-using agents

Agents that call your APIs to look up, create and update records securely.

Security & permissions

Per-user data access, prompt-injection defences and PII handling.

Evaluations

Test sets and automated scoring to catch regressions before release.

Cost control

Model routing, caching and token budgets that keep running costs predictable.

Custom interfaces

React widgets, in-app assistants, Slack/Teams bots, whatever fits your users.

How it works

From first call to live in weeks

  1. 01

    Technical scoping

    Requirements, data sources, security constraints and success metrics.

  2. 02

    Prototype

    A working slice on your real data within the first sprint.

  3. 03

    Build & evaluate

    Iterate against an evaluation set until quality targets are met.

  4. 04

    Ship & support

    Deploy, monitor and hand over, or keep us on retainer.

Best fit

Who this is built for

  • SaaS companies adding an AI assistant to their product
  • Companies with large document libraries or knowledge bases
  • Teams whose no-code chatbot hit its limits
  • Agencies that need a white-label AI development partner

Popular in

Works with your stack

No rip-and-replace. We integrate with what you already run.

OpenAIAnthropic ClaudeGoogle GeminiLangChainLlamaIndexPineconepgvectorSupabasePostgresNext.jsReactNode.jsPythonFastAPIVercelAWSSlackMicrosoft Teams

FAQ

AI Chatbot Developer FAQ

Straight answers to what buyers ask us most. Don't see yours? Ask on a free call.

Ask us directly

For a first production chatbot, an experienced agency is usually fastest and least risky: you get architecture, development, evaluation and deployment in one fixed scope. For ongoing product work, many clients keep us on a monthly engagement while their team ramps up.

Retrieval-augmented generation lets the chatbot search your documents and answer from them, rather than relying on the model’s general knowledge. If your chatbot must answer about your products, policies or data, you need RAG.

Yes. We regularly join existing repos, follow your conventions and CI, and work through pull requests your team reviews.

We build an evaluation set of real questions with expected answers, then score retrieval quality and answer correctness automatically, and track it on every change.

You do, code, prompts, evaluation sets and infrastructure configuration.

Taking projects for next month

Let's start something new together

Book a free 30-minute strategy call. We'll map the agents, automations and integrations worth building first, and tell you honestly what isn't.

No obligation Fixed-scope proposal You own the code