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Turn Your Data Into a Competitive Advantage

We design and deploy AI-powered products and data science systems that go live, scale, and drive real business outcomes — not just demos.

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Compliant with:

AWS Partner
GDPR
HIPAA Compliant
ISO 27001
DORA
AICPA SOC

Trusted by forward-thinking companies

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PwC
Toyota
Geberit
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Common challenges

AI projects that never reach production

Most AI initiatives stay in the demo phase. Teams prototype endlessly but lack the engineering infrastructure to turn models into reliable, production-grade services.
Valuable data is scattered across disconnected systems and formats, making it impossible to train accurate models or build consistent analytics pipelines.
Hallucinations, inconsistent answers, and opaque logic erode user confidence quickly — especially in regulated industries where accuracy and auditability are non-negotiable.
Unoptimized inference, bloated models, and poor architecture choices cause AI running costs to spiral before the product delivers enough value to justify the spend.
What we build

End-to-end AI and data science

From strategy to deployment — we cover the full spectrum of AI and data science capabilities.

AI Services

Custom LLM integrations, RAG pipelines, intelligent agents, and AI-powered features built to enterprise standards. We handle model selection, fine-tuning, evaluation, and production deployment.

Data Science

Predictive models, anomaly detection, recommendation engines, and analytics dashboards. We turn raw data into actionable insight — with reproducible pipelines and clear documentation.

AI Interface Layer

A managed abstraction layer that sits between your product and multiple AI providers. Swap models, A/B test prompts, track costs, and enforce quality gates — without rewriting your app.

Our AI products

Proven AI products you can deploy in your stack today.

KnowHub

Your company's AI knowledge assistant

KnowHub

KnowHub connects to your internal documents, wikis, and databases to give employees instant, accurate answers grounded in your own data — with full source attribution and audit trails.

Connects to Confluence, Notion, SharePoint, and custom sources

Role-based access control per document and knowledge domain

Full answer provenance with source citation

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KnowHub

InProduct AI

Embed AI assistance directly into your product

InProduct AI demo

InProduct AI adds an intelligent assistant layer to your existing SaaS or enterprise application. Users get contextual help, smart suggestions, and workflow automation — without leaving your product.

Conversational UI that adapts to your product's context

Triggered automations based on user behavior and intent

Transparent reasoning with confidence scoring

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InProduct AI demo

Smart Search

Semantic AI Search

A semantic search engine that understands what your learner is looking for, not just the words they typed.

Analyzes descriptions and comments, not just tags.

Understands intent and prioritizes conditions.

Verifies each requirement with a proof of fact.

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Legacy code to ChatGPT-like interface

AI legacy modernization

Upgrade your existing platform with a dynamic chat interface. Give users instant, natural-language access to your data without the need for a total system rewrite.

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AI legacy modernization

Why teams trust our AI

Verified Answers

Every AI response is grounded in your data and attributed to a source. No hallucinations, no guessing — just accurate, auditable outputs your users can act on.

Enterprise Security

GDPR-compliant infrastructure, end-to-end encryption, and role-based access controls built in from day one. Your data stays yours — never used to train third-party models.

Production-First Approach

We engineer for reliability, observability, and cost efficiency from the start. Monitoring, alerting, and performance budgets are part of every delivery — not an afterthought.

AI projects we've shipped

Cyber risk decision-making web dashboard—SSIC scalable platform for C-suite risk mitigation

Legacy Data into an AI-Powered Cybersecurity Management Platform

Securing Fortune 500 partnerships and tripling the corporate customer base through a millisecond-fast cybersecurity SaaS application.

View all case studies

Ready to move from experiment to production?

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Frequently asked questions

What kinds of AI projects does Startup House take on?

We work on a wide range of AI initiatives: LLM-powered features, RAG-based knowledge systems, semantic search, predictive analytics, recommendation engines, and custom AI agents. If it involves making a product smarter with data or language models, we're interested.

Do you work with OpenAI, Anthropic, or open-source models?

Yes — we're model-agnostic. We've deployed production systems using OpenAI GPT-4o, Anthropic Claude, Mistral, Llama, and fine-tuned domain-specific models. We recommend the best fit for your accuracy, cost, and latency requirements.

How do you prevent hallucinations in AI outputs?

We use retrieval-augmented generation (RAG) architectures to ground responses in your verified data, combined with output validation layers, confidence thresholds, and human-in-the-loop review flows for critical decisions.

Can you integrate AI into our existing product without a full rebuild?

Absolutely. We frequently add AI capabilities to existing applications via API integrations, embedded widgets, and microservice architectures. Our AI Interface Layer makes it easy to add, swap, or upgrade AI features without touching your core product.

How long does it take to go from idea to a working AI feature?

A focused AI feature (e.g., semantic search, a Q&A assistant, a classification pipeline) typically takes 4–10 weeks from kick-off to production deployment. More complex multi-model systems or data infrastructure projects run 3–6 months.

How do you handle data privacy and compliance?

We build GDPR- and HIPAA-aligned systems by default: data minimization, encryption at rest and in transit, audit logging, and clear data retention policies. We never send your proprietary data to third-party model providers for training purposes.

What's included in your AI & Data Science engagements?

Depending on scope, engagements include: problem framing and data audit, architecture design, model selection and evaluation, infrastructure setup, API and UI development, monitoring dashboards, documentation, and post-launch support.

We build what comes next.

Company

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Startup Development House sp. z o.o.

Aleje Jerozolimskie 81

Warsaw, 02-001

VAT-ID: PL5213739631

KRS: 0000624654

REGON: 364787848

Contact Us

hello@startup-house.com

Our office: +48 789 011 336

New business: +48 798 874 852

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