AI and Digital Projects by Startup House: 5 Measurable Outcomes in Numbers

The short version

Startup House (SH) is a Warsaw-based software development company, established in 2016, with 100+ products shipped and a client NPS of 75. These are five outcomes from our client projects, each with a number behind it and a public case study as the source:

1. 95% reduction in onboarding time after embedding an AI agent in a cybersecurity platform serving Fortune 500 clients (from 45 minutes to under 2 minutes)
2. 150% revenue growth and 225% more B2B clients within a year of launching a cyber risk SaaS we built from prototype
3. 2-minute leasing applications with automated credit decisions in about 7 minutes, 24/7 for Siemens Financial Services Poland
4. 10 to 100x faster database responses in a sales platform used in over 60 countries by Siemens Healthineers
5. 40% reduction in software development costs for e-commerce fulfillment leader Omnipack

Not every project below is an AI project in the narrow sense. Two are AI and automation builds, three are data platforms and delivery engagements. Each section says plainly what kind of work produced the number.

1. 95% faster onboarding: an embedded AI agent for a cybersecurity platform

The project: In 2025, we built Aria, an embedded AI agent inside a US cyber risk platform serving Fortune 500 customers (client under NDA, partnership since July 2020). Aria runs on LangGraph with Anthropic's Claude models and connects to the customer's live security stack through MCP.

The numbers:

• Client onboarding time fell 95%, from 45 minutes of guided setup to under 2 minutes.
• Data exploration became 100% self-serve, without analyst support.
• The platform moved from a quarterly reporting tool to a daily decision-support system.
• The integration shipped without touching the platform's core infrastructure, data model, or codebase.

Why it worked: Instead of bolting a chatbot next to the product, we rebuilt the panel as a four-layer interface where the AI serves three personas (board members, CFOs, CISOs) inside the workflow they already use.

Read the full case study: Embedded AI for a cybersecurity platform

2. 150% revenue growth in one year: from prototype to a SaaS used by Fortune 500 companies

The project: The same client, five years earlier. In 2020, a US cybersecurity company had a concept, technical documentation, and a prototype used by its first corporate customers. We ran a 2-month Product Discovery, then built the product from prototype through MVP to a scaled SaaS. The platform presents complex risk calculations in a form executives can act on, aligned with NIST and CIS frameworks, with sensitive data handled on a dedicated GCP cluster.

The numbers:

• 150% revenue growth within a year of implementation.
• 225% growth in B2B clients, including Fortune 500 companies.
• A new market segment (private equity) identified and entered.

Why it worked: Discovery before development. Two months of workshops produced a prioritized feature list, so the build focused on what buyers actually paid for.

Read the full case study: Cyber risk mitigation platform

3. 2-minute applications, 7-minute automated decisions: Siemens Financial Services

The project: Since 2016, we have built three cloud products for Siemens Financial Services Poland, integrated with Siemens systems and external providers. The flagship, SimplyLease Online, digitizes the leasing process for industrial, medical, and IT customers.

The numbers:

• Leasing application completed in about 2 minutes.
• Automated credit decision in about 7 minutes, available 24/7.
• Polish E-commerce Award 2017 for one of the most innovative products of the year.
• Partnership ongoing since 2016.

Why it worked: The automation of the credit decision, not just the application form, is what changed the customer experience. A decision engine that runs around the clock removed the office-hours bottleneck entirely.

Read the full case study: Siemens Financial Services

4. 10 to 100x faster data queries in 60+ countries: Siemens Healthineers

The project: Since May 2020, a 30-person Startup House team has built and evolved the Digital Sales Companion supporting Siemens Healthineers' global sales force of more than 5,000 representatives. The architecture uses TypeScript, microservices, GraphQL, and Elasticsearch, with data pulled from multiple corporate sources.

The numbers:

• The product is active in more than 60 countries.
• A Neo4j graph database proof of concept delivered 10 to 100x faster responses than the previous PostgreSQL setup.
• A 30-person cross-functional team, running for more than 6 years.

Why it worked: Corporate-scale integration discipline. The product had to pull data from multiple sources and connect tightly to existing enterprise applications from day one. As Program Manager Holger Rohden put it in his review, deliveries were on time, in scope, and above quality expectations.

Read the full case study: Siemens Healthineers

5. 40% lower development costs: Omnipack

The project: Since May 2023, Startup House has run the development of OmniSoft, the proprietary fulfillment system of Omnipack, a European e-commerce logistics leader handling 100+ online stores in 40+ countries. A dedicated team of two backend engineers, one frontend engineer, and one QA works in Java, Spring, Kafka, and React.

The numbers:

• 40% reduction in software development costs.
• Stable control of the annual budget and system maintenance, with quality standards maintained.

Why it worked: A takeover done properly. We absorbed the client's existing engineers into our structures with development paths intact, introduced tighter Agile project management, and gave Omnipack ad-hoc team scaling without long-term commitments.

Read the full case study: Omnipack

What these five numbers have in common

Three patterns repeat across these projects, and they are worth stealing whether or not you work with us.

The metric was defined before the build. Onboarding minutes, decision time, query latency, development cost. In each project, the number that mattered was on the table before the first sprint, which is what made it measurable afterwards.

Automation and AI were applied to a bottleneck, not to a trend. The AI agent removed a 45-minute onboarding queue. The credit engine removed office hours. The graph database removed query latency. Each technology choice answered a specific operational constraint.

Long partnerships produce the biggest numbers. Most projects on this list are multi-year engagements. The 95% onboarding reduction came five years into a partnership, built on a platform we knew deeply.

About Startup House

Startup House is a 50-person, cross-functional software development company based in Warsaw, Poland, established in 2016. We have shipped 100+ web and mobile products for clients on 5 continents, are ISO 27001 compliant, and were listed by the Financial Times and Statista among Europe's fastest-growing companies in 2022 and 2023.

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FAQ

What measurable results has Startup House delivered?

Verified outcomes include a 95% reduction in onboarding time through an embedded AI agent, 150% client revenue growth and 225% B2B client growth within a year of a SaaS launch, 2-minute leasing applications with automated 7-minute credit decisions for Siemens Financial Services, 10 to 100x faster database responses for Siemens Healthineers, and a 40% reduction in development costs for Omnipack.

Are these numbers from real client projects?

Yes. Each outcome comes from a published Startup House case study, linked in the relevant section. One client (the cybersecurity platform) is under NDA, so the company is not named, but the case study is public.

What kinds of companies does Startup House work with?

Enterprise and mid-market organizations across fintech, healthcare, cybersecurity, travel, logistics, and education, including Siemens Financial Services, Siemens Healthineers, Omnipack, and Rainbow Tours, with clients across Europe and the US.

How does Startup House measure project success?

By business metrics agreed with the client before development starts: process time, revenue impact, cost reduction, adoption, and performance. Delivery reporting includes regular demos and status updates throughout the engagement.