November 6, 2024 4:00 PM
CET
How to improve the security, scalability and intelligence of your access control
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Make every data decision one you can trust
IndyKite turns context into trust — governing how enterprise data is used, verifying it at the moment of use, and proving every decision. Power AI and digital operations on data you can stand behind.
Trusted by leading enterprises
What is data trust?
Data trust is the confidence that the data feeding your decisions and AI is accurate, governed, and used only as permitted — verified at the moment of use, not assumed. As enterprises pour more data into AI, unverified or ungoverned information quietly becomes risk. IndyKite captures the signals behind trust and continuously evaluates them through Trust Score, giving applications and AI a measurable indicator of confidence.
Trust evaluated continuously
Trust is evaluated the instant data is retrieved or used by AI, based on continuously updated trust signals rather than assumptions about where it was stored or who loaded it las
Governed end to end
Every dataset carries the context needed to govern its use, including purpose, restrictions, and conditions that remain consistent across systems.
Provenance you can prove
Know where data came from, how fresh it is, and how it was transformed, so decisions and AI outputs are grounded in verifiable trust
Sensitive data, safely mobilized
Context-aware controls allow sensitive data to be shared and used with confidence, preserving trust signals and governance across teams and partners.
Power trusted decisions at runtime
Apply live enterprise context and trust signals to queries, decisions, and actions in real time.
Govern data useacross teams, partners, and AI systems
Verify provenance and freshness before data drives a decision
Preserve trust when sensitive data is shared and used
Trace every data decision with full, queryable history
Trusted data in three steps
01
Connect your data and context
IndyKite builds a live knowledge graph of your data, identities, systems, and relationships, creating the context used to evaluate trust.
02
Attach trust signals to your data
Provenance, freshness, sensitivity, consent, and other trust attributes travel with the data itself. Trust Score continuously evaluates these signals to provide a measurable indicator of confidence.
03
Enforce and prove at the moment of use
Every query and decision is evaluated against live context in real time, with a complete, queryable record of what data was used, by whom, and why.
Hear from our customers
With IndyKite’s Platform, we will be able to support new and market-unique methods of onboarding and securing customers, inject more value for customer loyalty programs, drive new flexible payment and check-out solutions, and cross-brand benefits, ensuring our customers enjoy personalized, relevant, and rewarding experiences every time they engage.
Erik Torkildsen,
Head of Identity and Payments at Rema 1000
It’s helping PACCAR more quickly and reliably deliver value to our customers and make better decisions faster internally. We’re excited to be working with IndyKite.
Dallas Thornton,
Director Digital Services, Paccar
IndyKite’s platform offers the scalability, flexibility, and security needed to optimize our data management across our enterprise systems.
Ryan Carpenter,
Vice President, Commercial Programs & Operations at Rockwell Automation
IndyKite serving as an aggregator not only for Deutsche Telekom but for the entire CAMARA community and a broad range of services opens up possibilities for a range of clients that can benefit from accessing rich data they would not otherwise have access to - demonstrating the power of this initiative in action,
Peter Arbitter,
SVP MACE, a Deutsche Telekom initiative
Data trust questions
What is data trust?
Data trust is the confidence that the data feeding your decisions and AI is accurate, governed, and used only as permitted — verified at the moment of use rather than assumed. IndyKite continuously evaluates trust using live context, provenance, and Trust Score to provide a measurable indicator of confidence for every dataset.
How is data trust different from data governance?
Data governance defines policies and manages data assets. Data trust applies those policies together with provenance, context, and trust signals to determine whether information can be confidently used for a particular purpose.
How does IndyKite establish trust in data used by AI?
IndyKite evaluates data against a live knowledge graph, weighing signals such as provenance, freshness, sensitivity, and consent. TrustScore converts these signals into a measurable indicator of confidence, helping AI systems use only data that is verified, permitted, and fit for the task at hand
How do you securely share sensitive data across teams, partners, and ecosystems?
Context-aware controls allow organizations to securely share sensitive data across teams, partners, and B2B ecosystems while preserving governance, provenance, and trust. Data remains protected and appropriate use can be enforced consistently across organizational boundaries.
How does data trust support compliance and audit?
Every data decision is recorded and fully traceable, allowing organizations to prove what data was used, where it originated, under what conditions it was accessed, and why. By capturing provenance and maintaining a queryable history, IndyKite helps turn compliance into a continuous, provable process rather than a periodic review exercise.
How do we get started?
Most teams begin with a focused demo mapped to their own data sources and governance requirements. Book a demo and our team will scope a path to trusted data across your enterprise.
Build on data your enterprise can trust
Get a working view of context-aware data governance and real-time trust — mapped to your data sources and compliance requirements.
Talk to our team
