SOLUTION 06
AI SAFETY & GOVERNANCE
Trapped Between Two Undesirable Choices
Deploy AI Now, Govern It Later
Move fast against existing data, and plan to bolt on security, lineage and oversight once the model is already in production.
Lock Data Down, Delay AI
Restrict access to sensitive data so tightly that analytics and AI initiatives stall indefinitely, while pressure to innovate keeps building.
Neither works. AI adoption needs secure data foundations from day one — not governance added afterwards, and not data locked away entirely.
Ungoverned AI Amplifies Risk. Locked-Down Data Stalls Innovation.
AI Without Secure Foundations
- Amplifies existing data risk instead of reducing it
- Exposes sensitive fields to prompt injection and model poisoning
- Synthetic identity and deepfake fraud go undetected
- No lineage to trace what data trained or informed a model
Locking Data Down Entirely
- Analytics and AI initiatives stall indefinitely
- Business value from existing data assets goes unrealised
- Teams build workarounds to get the access they need anyway
- Board and regulator pressure to innovate goes unanswered
A Secure-Foundations AI Strategy
CCA and OpenText combine discovery, protection and auditable lineage so AI systems can safely draw on enterprise data — with governance built in from day one.
Secure Data Foundations Enable Safe AI
AI safety begins with data protection architecture, not model governance alone — sensitive data must be discovered, classified, encrypted and governed before it reaches an AI workflow.
Auditable data lineage means AI teams always know the source of the data feeding their models.
Significantly Reduces AI Risk
- Encryption and tokenisation let AI consume data without exposing raw values
- Automated discovery and classification cover legacy and modern platforms alike
- Governed, policy-controlled access keeps AI systems operating on trusted data
- Auditable lineage supports explainability and regulatory assurance
Safe AI, End to End
Discovery, protection and lineage enforced before data ever reaches a model.
Enterprise Data
Legacy & modern platforms
Discover, Protect & Trace
Classification, encryption, lineage
AI & Analytics
Trusted, governed inputs
Purpose-Built Components, Working as One
Rocket Data Replicate and Sync (RDRS)
Real-time change data capture and synchronisation across legacy and modern environments, as changes occur.
OpenText Voltage SecureData
Encryption, format-preserving encryption, tokenisation and policy-driven controls — without impacting usability.
CCA Secure Data Connector
Integrates real-time replication with protection services so sensitive data stays protected throughout synchronisation.
OpenText Voltage Data Security Platform (DSP)
Discovers and automatically classifies structured data assets — what exists, where it resides, and how it should be governed.
Rocket Data Intelligence, Insight and AI
Auditable data lineage integrated with RDRS — so teams always know the source of the data feeding their AI models.
What the Solution Delivers
Data Discovery & Classification
Automated identification of sensitive structured data across legacy and modern platforms.
Encryption & Tokenisation for AI
Lets models and analytics consume protected data without exposing raw values.
Auditable Data Lineage
Traces the source of every dataset feeding an AI workflow, supporting explainability.
Governed, Policy-Controlled Access
Keeps AI systems operating on trusted, compliant data assets.
Outcomes That Matter to the Business
Build Secure Foundations Before Scaling AI
Make Enterprise Data Available Without Exposing It
Support Explainable, Auditable AI
Reduce New AI-Driven Attack Surfaces
Maintain Public & Regulator Trust
Build AI foundations that are safe today, and ready for tomorrow.
Talk to a consultant about embedding secure data architecture into your AI roadmap.
Talk to a consultant
