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AI Integration & Workflow Automation

Connect AI to your real data — documents, CRMs, databases, and operational workflows.

Key Capabilities

  • Custom LLM integrations with your data (RAG pipelines)
  • Document analysis, extraction, and classification
  • AI-powered search across internal knowledge bases
  • Workflow automation connected to CRMs and ERPs

Technology Stack

PythonLangChainOpenAIPineconeFastAPIPostgreSQL

Best forOperations Teams, Professional Services, Enterprise

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overview

We build practical AI systems that plug into your existing data and processes. That means AI connected to your internal documents, CRM records, support tickets, databases, and ERPs — not generic chatbots, but systems that understand your business context and reduce manual work.

Network cabling in a rack lit green

Key Capabilities

  1. Custom LLM integrations with your data (RAG pipelines)
  2. Document analysis, extraction, and classification
  3. AI-powered search across internal knowledge bases
  4. Workflow automation connected to CRMs and ERPs
  5. Reporting assistants and data summarization tools
  6. Predictive scoring and recommendation systems

how we work

How a project runs

Five stages. Each one ends with something you can read, click or use.

  1. Step 01

    Discovery call

    A 30–45 minute conversation about what you're trying to change and what's slowing it down today. Technical detail is welcome but not expected.

    You get

    A written summary of the problem as we understood it.

  2. Step 02

    Scope and proposal

    We break the work into deliverables, decide what belongs in the first version and what can wait, and put a price on it.

    You get

    A scope document, a delivery plan and a fixed price.

  3. Step 03

    Design and architecture

    Interface flows and technical architecture are decided together, so what gets designed is something that can actually be built and maintained.

    You get

    Clickable screens and a technical plan.

  4. Step 04

    Build

    Development runs in two-week cycles. Each one ends with a working version on a test environment you can open yourself.

    You get

    A running version every two weeks.

  5. Step 05

    Launch and after

    We deploy to production, set up monitoring, train your team, and stay on through the agreed support period.

    You get

    A live system, documentation and a support window.

Not sure which of these you need?

Describe the problem in a few sentences. We'll tell you what we'd build, what it would cost, and whether we're the right team for it.

Tell us about your projectHow we work

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