AI That Ships, Not Just Demos

D-Factor helps engineering teams adopt AI tooling that fits their stack, their workflows, and their delivery pace — from LLM integration to automated code review and beyond.

What We Bring to Your AI Rollout

Engineers Who Have Done It

Our consultants have implemented LLM integrations, RAG pipelines, and AI-assisted workflows in production software — not just evaluated them in slide decks.

Stack-Agnostic, Vendor-Neutral

We assess what fits your existing infrastructure and team capability — not what we have a partnership incentive to sell. Model selection, API choice, and hosting decisions are made for your context.

Focused on Delivery, Not Discovery

Engagements end with running code, documented patterns, and a team that knows how to maintain and extend what was built — not a report with a list of opportunities.

Data and IP Handled Correctly

Every integration is designed with data residency, access control, and IP ownership in mind. No training on your proprietary data without explicit agreement.

How an AI Rollout Engagement Works

Week 1

Scope and Audit

We map your current stack, team workflows, and delivery pain points. We identify where AI tooling creates real leverage — and where it creates noise.

Week 2

Tooling Selection

We evaluate and recommend specific tools, APIs, and integration patterns. Output is a concrete implementation plan, not a vendor comparison matrix.

Weeks 3–6

Implementation

Our engineers integrate the selected tooling into your codebase. This includes prompt engineering, retrieval pipeline setup, evaluation harness, and developer documentation.

Week 6+

Handoff and Support

Your team takes ownership. We provide a handoff session, runbook, and optional retainer for ongoing tuning as models and usage patterns evolve.

From Our Blog: Applied AI

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Frequently Asked Questions

What kinds of AI use cases do you work on?

Primarily: LLM integration into existing products (search, generation, classification), AI-assisted developer tooling (code review, documentation, test generation), and RAG pipelines over internal knowledge bases. We do not build foundational models or run large-scale ML research.

Do you work with OpenAI, Anthropic, or other providers?

How long does a typical engagement take?

Can you work with our existing engineering team?

Get in touch

Contact us

Leave your request in the form or book a call with our specialists. After that you can get a free consultation on your project or direct access to our verified staff database.

+48 888 420 245 info@d-factor.pro