# Sparkbit > Sparkbit is a reviewed AI agency in Warsaw, Poland, listed in the AIAgencies.eu register and last assessed 2026-09-23. Canonical page: https://www.aiagencies.eu/agency/sparkbit Generated: 2026-09-28 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold. ## Facts - Location: Warsaw, Poland - Website: https://www.sparkbit.pl - Hourly rate: €85-130/hr (directory-listed) - Team size: 10-49 - Founded: 2014 - Services: AI Consulting, AI Development - Industries: Healthcare, Manufacturing, E-commerce - LinkedIn: https://www.linkedin.com/company/sparkbit ## About Warsaw software house delivering machine-learning systems and R&D prototypes, with a research-heavy team drawn from Polish scientific universities. Works computer vision, time-series and retrieval problems alongside backend architecture. ## Documented clients Documented engagements: 5x5 Technologies, phy, Italist, Spicerr, and Altermobili. All 5 carry a source URL on file. ## Curator assessment Reviewed 2026-09-23 by Gabor Kiss against published evidence. Sparkbit publishes ML case studies with the model, the metric and the handover spelled out: for 5x5 Technologies it retrained a YOLOv8 tower-equipment detector from F1 0.72 to 0.86 over a 12-month engagement on a telecom digital-twin platform, and for the New York health-tech startup phy it built a posture-analysis core covering 20+ conditions whose algorithms went into the client's FDA application. The studies also show where work stopped: the anti-counterfeit label project ended after discovery when the findings argued against continuing, and the context-aware telematics system was a grant-funded R&D program whose hardware rollout, the study says, was held back by the supply chain. Most dated AI work falls in 2020–2022; the LLM-era record is an anonymized RAG assistant over 7,000+ PDFs for a Swiss device manufacturer (2025), described as in production, and an Italist data-quality pipeline whose GPT-4 stack sits under a 2020–2022 label. The weaker fit is buyers who need business outcomes measured in money or hours—results here are model metrics and qualitative gains—or a named reference for a recent LLM deployment. ### Key strengths - Model metrics are published with the stack: F1 0.72 to 0.86 at 5x5, about 0.85–0.95 F1 on key telematics perception functions, and ~8k concurrent users sustained with under 0.002% timeouts - Five client executives are quoted by name and title—including 5x5 Technologies' CEO, Italist's CTO and Spicerr's CEO—four of them on the case study their quote refers to - The services page lists what is handed over—repos, infrastructure-as-code, test suite, dashboards, runbooks and IP assignment—and the 5x5 study reports that handover took place ### Good to know - No founder or engineer is named anywhere on the site—ask who would lead your project and to see that person's prior ML work - The Italist study lists GPT-4 while the index dates it 2020–2022 and files it under Health-tech—ask for the dates and scope of the LLM work specifically - Outcomes such as "duplicates down" and "operational savings" carry no figures—ask each reference what the system changed in hours, cost or error rate ## Compared head-to-head - Sparkbit vs Algomine: https://www.aiagencies.eu/compare/algomine-vs-sparkbit - Sparkbit vs deepsense.ai: https://www.aiagencies.eu/compare/deepsense-ai-vs-sparkbit --- Source: AIAgencies.eu — the curated register of European AI agencies. Rate provenance: "agency-confirmed" = disclosed via submission or claimed profile; "directory-listed" = Clutch or two agreeing B2B directories (lone unverified sources are never written). Full method: https://www.aiagencies.eu/methodology · Rate index: https://www.aiagencies.eu/rates