Test AI ideas fast.
Fund the ones that work.

Innovify AI Labs is an on-demand proof-of-concept team for enterprise innovation leaders. We shortlist your AI ideas, build several working proofs of concept in parallel, test them with real users, and hand over the evidence you need for a funded business case, then take the winners from pilot to production.

Innovify AI Labs builds GenAI applications, agentic workflows, RAG systems, predictive models, personalisation engines, fraud and risk systems, digital twins and end-to-end MLOps pipelines.

An in-house team knows your business but rarely has spare capacity for experiments. A big consultancy suits large transformation programmes but is often heavier than a small experiment needs. An AI innovation lab like Innovify AI Labs fits when you want to test several ideas quickly with real users and build the business case without hiring. Many enterprises combine them: the lab proves the idea, the in-house team runs it.

Yes. Innovify AI Labs specialises in building AI systems that are production-ready, including deployment, monitoring, retraining, security and performance optimisation through robust MLOps practices.

Yes. Innovify AI Labs helps organisations define AI opportunities, validate use cases and test feasibility through structured experimentation before scaling solutions into production systems.

Yes. Innovify AI Labs designs and deploys GenAI solutions including LLM applications, RAG pipelines, copilots, virtual agents and domain-specific AI systems.

Innovify AI Labs implements full MLOps pipelines covering model training, deployment, monitoring, retraining, versioning and governance to ensure AI systems remain reliable over time.

Yes. Innovify AI Labs has experience delivering AI systems in regulated and high-risk environments, including fintech, payments, fraud, risk and compliance-driven domains.

Yes. Innovify AI Labs continues to support AI systems post-deployment through monitoring, optimisation, retraining and platform evolution as data, usage and scale change.

Innovation and transformation leaders who have more AI ideas than delivery capacity. We help you test the most promising ideas quickly, compare the results and take only the proven ones forward.

Engagements usually begin with a discovery and use-case definition phase, followed by validation, system design and production deployment based on business goals.

A small, working version of an AI idea, built to test whether it works with real users or data before you invest in a full build.

Yes. We can prototype a shortlist of ideas side by side so you can compare them on the same success measures.

Yes. Innovify AI Labs acts as your on-demand team, from scoping and design to build, testing and reporting.

Working prototypes, test results against the agreed success measures, and the evidence you need for a business case.

An AI-native partner designs products around AI from the architecture up — data pipelines, model governance, guardrails and human-in-the-loop controls — rather than adding AI features to an existing build. Innovify embeds these from discovery through deployment, with audit trails and compliance built in.

Design for production from the first sprint: agree success measures with the business, keep data handling and model decisions auditable, involve risk and compliance early, and build on architecture that can be hardened rather than rebuilt. Innovify builds PoCs this way, so a proven idea can move into production without starting again.

Usually not because the model fails. Common causes are no agreed success measures, no budget owner for the next stage, data that is not production-ready, and governance left until the end. Setting the business case, data access and compliance path at the start avoids most of these.

Compare every PoC on the same measures agreed up front: user response, business value, feasibility with real data, and the cost and risk of running it at scale. Scale the ones that clear the bar, stop the rest early, and record why, so the evidence feeds the next round of ideas.

Yes, several. For ARM, Innovify made a self-serve SoC design platform AI-native, with guided decision support and embedded engineering knowledge. PolicySmart's AI-native claims platform cut claims processing time by 65%, with 95% accuracy in AI-driven data extraction. Animus's AI-native healthcare knowledge platform cut document processing and query response times by 60%. Innovify also built Orbis's AI compliance platform, tracking regulation across 50+ EU sources, a big-data and machine learning platform for Vonage, and took Canaree, an AI-driven product for private equity, from build to launch.