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Custom AI Built for Your Data. Shipped to Production.

AI development services for enterprise teams that need a partner to build custom AI from concept to production. We assemble the engineering team, run the discovery, ship the system, and stay through deployment. Grounded in your data, never trained on it.

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Trusted by enterprise teams across Europe and the US.

Siemens
Siemens Healthineers
PwC
Toyota
Geberit
Rainbow
Chooose
Omnipack
Lexolve

Do any of these

sound familiar?

We need AI in our business but don't know where it fits.
We have a clear AI use case but no team to ship it.
We need senior AI engineers in weeks, not 6 months.
We can't tell if our use case needs RAG, fine-tuning, or both.
Our PoC worked. Scaling it broke things we didn't see coming.

We cover the full custom AI development stack:

Every system we build is grounded in your data, never trained on it. Built to ship, not to demo.

AI Interface Layer for Legacy Systems

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

Generative AI Prototyping (PoC)

Validate your ideas quickly with functional prototypes to minimize investment risk.

LLM & AI Agent Development

Build sophisticated agents that understand context, follow procedures, and execute tasks.

Custom AI Product Development

From initial concept to a fully operational platform.

AI Chatbots & Knowledge Platforms

Transform static documents into interactive, 24/7 experts for your team or clients.

Data Preparation & Processing

Your AI is only as good as the data feeding it. We ensure peak performance and reliability through expert data cleaning, structuring, and optimization.

How Custom AI Development Works at SH

01

Discovery

We start with the business problem, not the technology. We map your data, your infrastructure, your compliance constraints, and the specific outcome you're measuring. Then we define what success looks like in measurable terms before any engineer writes a line of code.

Use case definition with success metricsData and infrastructure assessmentArchitecture proposal with technology selection (RAG, fine-tuning, agents)

02

Build

We assemble the engineering team and start shipping. Senior AI engineers, ML specialists, and data engineers work in your sprint cadence with your tools. Weekly demos, transparent progress, no black-box delivery. AI-augmented development workflows where the engineering team uses internal AI tooling to ship faster without cutting corners.

Working system grounded in your dataIntegration with your existing infrastructureSprint reviews and weekly progress demos

03

Validate

We test the system against your real data, your edge cases, and your compliance requirements. Hallucination tests, accuracy benchmarks, security audits, and load testing before anything reaches production users. If something doesn't hold up, we fix it now, not after launch.

Accuracy and hallucination test resultsSecurity and compliance audit reportLoad and performance benchmarks

04

Deploy & Monitor

We deploy to production, integrate with your monitoring stack, and stay through the first weeks of live traffic. Model drift monitoring, retraining schedules, and post-deployment optimization are part of the engagement, not an upsell.

Production deployment with monitoring dashboardModel drift and retraining schedulePost-deployment optimization plan

Why Enterprise Teams Choose SH for AI

Verified Answers, Always

Every AI system we ship is grounded exclusively in your verified data: your codebase, your documents, your database. The AI cannot generate answers from public training data or invent facts. Every response is traceable back to the exact source. For enterprise teams shipping AI to regulated users, that traceability isn't optional, it's the entire point.

Enterprise-Grade Security

ISO 27001 certified. Your data never trains another model. We integrate with your SSO and access policies, encrypt at rest and in transit, and restrict database access to within the application. Compliance with GDPR, HIPAA, SOC 3, DORA, and NIS2 is built into how we ship, not added at the end.

Production-First, Not Demo-First

We build AI that ships, not AI that wins demos. Our engagements end with monitored, deployed systems that hold up to real enterprise traffic. Cyber Risk Mitigation Platform: 400% B2B client growth post-AI integration. Siemens Financial Services: 24/7 automated credit decisions in 7 minutes. We measure outcomes, not capabilities.

AI in Production

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.

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Why Enterprises Choose Us

We're a 50-person, cross-functional software development team based in Warsaw, Poland, building technology that delivers ROI, strong governance, and real adoption.

0

years delivering digital products

est. 2016

0+

products shipped

web & mobile

0+

experts on board

Product & UX designers, Software engineers, AI specialists, PMs

0

client NPS

Praised for communication, pace and quality

0

continents served

North America, South America, Europe, Asia, Africa

How do we secure your data?

ISO 27001 compliance

We operate under ISO 27001 certified security practices across all client engagements.

Your data stays yours

We do not use your data to train our AI Assistant or any other model.

SSO & access policy integration

We integrate with your SSO and access policies for seamless, compliant user management.

Code and repository only

We work exclusively with your code and repositories, never with external data sources.

Encryption at rest and in transit

All data is encrypted at rest and in transit to meet enterprise security requirements.

Most enterprise AI projects fail not because the model is wrong, but because the partner can't ship it. We measure success by what runs in production, holds up to real traffic, and earns user trust. Demos don't ship to enterprise users. Engineering does.

Alex Stasiak

Alex Stasiak

Co-Founder at Startup House

Ready to Build AI That Ships to Production?

Tell us your use case, your data, and your timeline. We'll tell you what it takes to build it.

Book a 30-min Call

A team trusted by best-in-class companies.

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Frequently Asked Questions

What's the typical AI development process at SH?

Custom AI development at SH runs in four phases: Discovery (use case definition, data and infrastructure assessment, architecture proposal), Build (engineering team assembled, weekly demos, integration with your systems), Validate (accuracy testing, hallucination tests, security audit, load testing), and Deploy & Monitor (production deployment, monitoring stack integration, model drift monitoring). Every phase ends with concrete deliverables, not progress reports. The team that runs discovery is the team that ships the system, so context never gets lost between phases.

How do I hire an AI development team for a custom project?

For a custom AI project, you typically need senior AI engineers, ML specialists, a data engineer, and a delivery lead. Hiring this team in-house takes 4 to 6 months and significant ongoing cost. Working with SH gives you a complete AI engineering team in 2 to 4 weeks. We assemble the team based on your use case, your stack, and your compliance requirements. Mid-level and senior engineers only, never juniors. The team works in your sprint cadence and stays through deployment.

How long does custom AI development take?

Timelines depend on scope, data complexity, integration requirements, and compliance constraints. Honest answer: it depends. Reference points: a focused proof of concept runs 2 to 4 weeks. A custom AI feature inside an existing platform typically runs 8 to 16 weeks. End-to-end custom AI product development, from discovery to production, typically runs 12 to 24 weeks. Complex enterprise AI systems with regulated data and deep integrations can run 6 to 12 months. We give you a precise estimate after a discovery call, scoped to what you're actually building.

How much does custom AI development cost?

AI development cost depends on scope (how much you're building), complexity (regulated industry, real-time data, deep integrations), and timeline (parallel teams ship faster but cost more). For reference, a generative AI proof of concept runs 30,000 to 80,000 EUR. A custom AI feature inside an existing platform runs 80,000 to 250,000 EUR. End-to-end custom AI product development runs 200,000 EUR to several million depending on scale and ongoing development. We scope precisely after a discovery call so the estimate matches what you're actually building, not a generic price list.

Can you augment our existing AI team rather than build the whole project?

Yes. We work in two modes. End-to-end custom AI development where we own delivery, and AI team augmentation where we embed senior AI engineers into your existing team. For augmentation, we match engineers to your stack, role, and project, run interviews with your team, and onboard within 2 to 4 weeks. AI team augmentation is the right call when you have an internal AI team that needs more capacity or a specific skill set (LLM, agents, RAG, MLOps) you don't have in-house.

What technologies and frameworks do you work with?

We build with the technology that fits the use case, not the one we have the most experience with. Common stack: OpenAI, Anthropic Claude, open-source LLMs (Llama, Mistral) for self-hosted deployment, LangChain and LangGraph for agent orchestration, vector databases (Pinecone, Weaviate, pgvector), Python and TypeScript for application code, FastAPI and Node.js for backend services. We're cloud-agnostic and certified on GCP, AWS, and Azure. Technology selection happens during discovery based on your data, infrastructure, and compliance constraints.

How is custom AI development different from buying an AI product?

Buying an AI product gives you a working system fast, with a fixed feature set and limited customization. Custom AI development gives you a system designed exclusively for your use case, your data, and your business logic, but takes longer and costs more. SH builds both. Our proprietary AI products (KnowHub, SmartSearch, InProduct AI) cover common enterprise use cases like knowledge management, semantic search, and SaaS copilots. Custom development is the right call when your use case is unique, your data has constraints standard products can't handle, or your competitive advantage depends on the AI itself, not just having it.

We build what comes next.

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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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