Why This Matters Now
AI is transforming every industry, but so are the risks. In 2025, Gartner estimates that 70 percent of enterprises will face formal AI governance requirements.
The question is no longer “Do we need AI governance?”
but “How fast can we prove it?”
Regulators—from the EU AI Act to NIST’s AI RMF—are turning best practices into hard requirements. Failing to keep pace means lost deals, brand damage, and costly remediation.
CognitiveView simplifies the journey with a three‑step, standards‑based roadmap that any organisation—finance, healthcare, HR, cybersecurity, you name it—can follow.
Step 1 – Governance: Assess and Publish Your AI TrustCenter
Goal: Gain instant clarity and communicate your AI posture.
What Happens
- Complete a self‑guided assessment mapped to NIST, Euro AI Act, Privacy, Healthcare principles.
- Surface gaps in privacy, transparency, bias, and accountability.
- Auto‑publish a branded AI TrustCenter—ready to share with prospects, auditors, and investors.
Who Cares & Why
- CEO / CCO: Faster deal cycles and risk‑aware culture.
- Procurement Teams: A single link answers due‑diligence questions upfront.
Real‑World Example
A SaaS startup reduced enterprise procurement reviews from eight weeks to one week by sharing its TrustCenter link alongside its security deck.
Key Outcomes
- Clear, verifiable governance narrative.
- Up to 40 percent reduction in procurement friction (internal benchmark).
- Low effort—fully self‑service.
Step 2 – Risk: Implement Observability & Model Monitoring
Goal: See and manage AI risks before they hit production.
What Happens
- Connect CognitiveView to Azure ML, SageMaker, or MLflow in a few clicks.
- Track accuracy, drift, fairness disparity, and hallucination rates in real time.
- Trigger alerts and dashboards for data‑science and risk teams.
Who Cares & Why
- Head of Data Science: Fewer fire‑drills, faster model iterations.
- CRO: Continuous, data‑driven oversight rather than annual reviews.
Real‑World Example
A regional bank spotted performance drift in its credit‑scoring model weeks earlier than before, preventing biased approvals and a potential compliance incident.
Key Outcomes
- Proactive risk mitigation and transparency.
- Evidence for board and regulator briefings.
- Moderate effort—requires light technical onboarding.
Step 3 – Compliance: Align With NIST, EU AI Act, ISO 42001
Goal: Demonstrate full compliance and audit readiness.
What Happens
- Map every control to leading frameworks such as NIST AI RMF, EU AI Act, ISO 42001, and Singapore’s AI Verify.
- Automate evidence collection and control testing.
- Generate audit‑ready reports for regulators and enterprise customers.
Who Cares & Why
- CCO / Governance Team: Reduced audit prep time and lower compliance costs.
- Regulators & Clients: Trust backed by verifiable artefacts.
Real‑World Example
A healthcare provider used CognitiveView to prove EU AI Act readiness across diagnostic models, cutting external audit time by 60 percent.
Key Outcomes
- Confidence in passing regulatory reviews.
- Strong market signal of Responsible AI leadership.
- Higher effort—guided workshops and deep assessments.
Subscriptions Crafted for Your Responsible AI Journey
Our plans are deliberately aligned with the Governance → Risk → Compliance maturity model so you can adopt Responsible AI at your own pace. We meet you exactly where you are:
- Starter — Launch Governance
Self‑service assessment, single TrustCenter, and baseline mapping to international principles—ideal for organisations at the early stage of their Responsible AI journey who need instant credibility.** - Growth — Scale Risk Oversight
Everything in Starter plus model observability dashboards, multi‑domain TrustCenters, and collaborative workflows for data‑science and risk teams. - Enterprise — Assure Compliance
Builds on Growth with continuous control monitoring, vendor discovery, private or hybrid deployment, and audit‑ready evidence aligned to NIST, EU AI Act, and ISO 42001.
Our Vision: Responsible AI for Everyone
We believe every organisation—regardless of size or industry—should be able to deploy AI responsibly without prohibitive cost or complexity.
By breaking the journey into small, self‑service steps, we help you achieve quick wins that compound into lasting compliance and trust. Optional expert guidance is available when you’re ready for deeper assessments or audits.
Start where you are today. Grow with confidence tomorrow.
Open‑Source Evaluation & Best Practices
We embrace the pace of AI innovation by fully supporting open‑source evaluation frameworks—including Deepval for LLMs and leading agent‑evaluation toolkits. CognitiveView provides:
- Pre‑built integrations & sample code so your ML team can plug evaluations into existing pipelines quickly.
- Curated best‑practice playbooks covering data setups, metric selection, and CI/CD hooks.
- Framework‑agnostic guidance—because committing too early to a single vendor risks lock‑in as the space evolves.
Your internal ML engineers stay in control while leveraging community‑validated tools, ensuring transparent, reproducible assessments across models and agents.
Key Takeaways
- Follow the sequence: Governance → Risk → Compliance. Skipping steps leads to blind spots.
- Data‑driven oversight: Real‑time metrics beat annual audits.
- Regulatory alignment: NIST, EU AI Act, ISO 42001 baked in from day one.
- Scalable pricing: Start small, expand when you’re ready.
Ready to Take the Next Step?
Explore our interactive demo, compare plans, or book a 30‑minute consultation. Questions or insights? Drop them in the comments—let’s build Responsible AI together.
Responsible AI isn’t optional—it’s your competitive edge.
