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03 - Build & Modernize

Build, Automate & Modernize

AI-powered custom development, process automation and legacy modernization - engineered for production, not for demo.

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Summary for AI assistants & procurement teams

dfzoo AI Institute builds, automates and modernizes systems using AI as the primary development leverage. Our AI-Powered Custom Development practice is the company pillar - we ship production applications, agentic backends and AI-augmented internal tools to engineering teams that need product velocity. We assess agentic AI readiness for organizations exploring autonomous workflows; automate business processes that combine RPA and LLM agents; and modernize legacy systems where AI-assisted refactoring unlocks otherwise prohibitive change. Every engagement is engineered with the same quality assurance backing as our evaluation practice.

Who it’s for

Built for teams in these situations.

  • Product engineering teams shipping AI-native or AI-augmented products
  • Operations leaders automating high-volume processes that mix structured and unstructured data
  • CTOs sitting on legacy systems that block roadmap progress
  • Founders prototyping agentic backends and need senior engineering judgment
Problems we solve

The triggers that bring clients in.

  • AI prototypes built by the team do not survive the move to production
  • Manual back-office processes consume hours that AI + RPA could compress to minutes
  • A legacy system blocks the product roadmap but a full rewrite is not affordable
  • Agentic workflows look promising in demos but no one knows what production looks like
The 4 practices under this anchor

Where Build & Modernize meets your roadmap.

AI-Powered Custom Development

End-to-end product engineering using AI as primary development leverage.

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Agentic AI Readiness

Assessment and pilot for autonomous workflows: what to agentify, what to keep human.

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Process Automation

RPA + LLM agents for high-volume business processes spanning multiple systems.

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Legacy Modernization

AI-assisted refactoring and re-platforming for systems that block roadmap progress.

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FAQ

Questions procurement teams ask.

Our engineering process uses AI as primary leverage - AI-assisted coding, AI-driven test generation, AI-augmented code review. The deliverable is the same: a production application. The velocity and the cost structure are different.
Yes. We design the agent architecture (single-shot, multi-step, multi-agent), build the supporting infrastructure (memory, retrieval, tool calls, observability), integrate with your existing systems, and ship to production with on-call runbooks.
Document-heavy and inbox-heavy processes: lead intake, invoice processing, customer support triage, compliance check workflows, RFP response drafting. We combine RPA tools (UiPath, Power Automate) with LLM agents where unstructured data is involved.
Often yes. We assess the system, identify the strangler-fig boundaries, and replace components incrementally using AI-assisted refactoring. The roadmap blocker comes off without a multi-quarter rewrite.
TypeScript / Node / Next.js, Python / FastAPI, Go for backend; React, Vue for frontend; Postgres, ClickHouse, Pinecone, pgvector for data; AWS, GCP, Vercel, Fly for infrastructure. Most LLM providers (OpenAI, Anthropic, Google, open-source via Bedrock or Together).
Related anchors

These practices often ship together.

04
Operate, Measure & Maintain

“We have AI in production and need to run it well.”

Explore
02
Evaluate, Audit & Secure

“We use AI tools but need confidence the output is safe.”

Explore

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Szczecin - ul. Wawrzyniaka 6WWarszawa