We’ve trained >80% of the world’s top AI models. Now, we’ll make them work for you.

Power is fewer, smarter moves.

Banks embraced AI by hiring geniuses and burying them in red tape. The result was theater, not transformation.

Done right, AI finds fraud, smooths ops, and makes service less robotic. But most firms still confuse headcount with horsepower.

Use cases

See how leading firms are streamlining operations and scaling insight.

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Customer service bots

Perform Know Your Customer checks with minimal human involvement.

Regulatory monitoring

Summarize new regulatory changes and assesses their operational impacts automatically.

Anomaly detection

ML models detect patterns of fraudulent transactions faster than traditional rules engines.

Predictive asset value forecasting

AI uses real-time data and alternative datasets to anticipate valuation swings.

Dynamic pricing models

AI models adjust loan or insurance product pricing based on real-time risk and customer profile data.

Explainability reporting

Provides transparent, auditable logic paths for AI-driven decisions to satisfy regulatory scrutiny.

Trusted by

Invisible helped Nasdaq streamline a data integration process, reducing customer onboarding time and saving 10,000 developer hours.

Invisible improved Cohere’s data quality and scalability, enhancing multilingual, coding, and reasoning capabilities to strengthen its enterprise-ready AI performance.

Invisible automated processes like invoice reconciliation, W9 processing, claim approval letters, and compliance support, resulting in significant cost and time savings.

Invisible's team worked within the client's platform to review model conversations from the research team and assess the level of accuracy of the model responses.

Invisible's team stepped in to review partially completed conversations between different models. We analyzed the search results, reference material, and model responses.

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We’ll walk you through what’s possible. No pressure, no jargon — just answers.