Unolabs is a data and AI engineering company that builds governed cloud data platforms and production-ready AI systems for large enterprises. The firm accelerates AI initiatives from pilot to production in 16–24 weeks through accelerator-led delivery, enforcing data quality SLOs and observability on every pipeline. Unolabs emphasizes architecture-led evolution and governance-first modernization, ensuring client teams can independently own and operate the platforms after handover.
Funding
Funding not disclosed
Founders
Product
Problem
Large enterprises often struggle to move AI initiatives from pilot to production, hampered by fragmented data systems, stalled modernization programs, and multi-year consulting engagements that deliver slide decks rather than working code. AI deployments without proper governance create operational risk, and traditional consulting models leave organizations dependent on external vendors long after the engagement ends.
Solution
Unolabs designs, builds, and transfers governed cloud data platforms and production AI systems that enterprises fully own. The company delivers its first production wave in 16–24 weeks by combining accelerator-led engineering with architecture-first methodologies. Unolabs enforces data quality service-level objectives on every pipeline and embeds observability across all production systems, ensuring reliability and compliance. Engagements are outcome-driven, producing production code and infrastructure rather than frameworks, and conclude with the client's team independently operating the platform without vendor dependency.
Target Audience
Primary customers are enterprise data and IT leaders at large organizations who need to modernize fragmented data estates, implement governed AI, and achieve production outcomes rapidly across industries such as consumer packaged goods and utilities.
Features
- Accelerator-led engineering delivery that compresses time-to-production to 16–24 weeks for the first production wave
- Architecture-led evolution with governance-first modernization, embedding metadata governance and compliance controls into the operating model
- Data quality SLOs enforced on every pipeline, with real-time observability systems for operational resilience
- Deep SAP modernization capability spanning S/4HANA transformation, BW warehousing, data integration, and BI BusinessObjects
- Interoperable ecosystems bridging SAP, Azure, Databricks, and modern cloud foundations
- Architectural expertise across data strategy, AI readiness, real-time streaming, migration factory, and agentic AI services