Invisible Technologies announces $100 million fundraise
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We’ve trained >80% of the world’s top AI models. Now, we’ll make them work for you.
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Spot sooner. Exit smarter.

Targets are noisy; signals are faint. Surface them sooner, track them relentlessly, and let proven plays propagate.

Insight compounds; multiples follow.

Certified and compliant.

Our commitment to enterprise-grade security is one reason nearly every major foundation model has relied on Invisible to accelerate the development of their AI applications.
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Use cases

See how leading firms are streamlining operations and scaling insight.

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PortCo data reporting

Create data models and processes that unify portfolio reporting, aggregate KPIs, and automate pipelines to track performance.

Compliance and risk reporting

Standardize data sources & reporting templates, automate data flows, and ingest qual / quant data at scale to improve accuracy and reliability.

Operations optimization

Streamline document handling, data entry, and reporting to free across marketing, finance, and client services teams for higher-value work.

LP relations

Automate communications, performance summaries, and data pulls, tailoring insights to investor profiles and enhance transparency during fundraising cycles.

Our approach

We embed with your team, observe how work flows, and build systems that align with what’s already in motion.

Trusted by

Invisible delivered a faster, more accurate AI investment assistant at 90% lower cost that unlocked real-time insights.

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

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

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.