- Your Greatest AI Risk Isn't Data. It's Knowledge
The Future of Enterprise Security is Knowledge Security
- THREE ENTERPRISE AI GAPS
The Three Challenges Enterprise AI Creates
AI can expose sensitive knowledge without triggering traditional security controls. These risks emerge through context, agent chains, and tools operating outside security visibility.
01
— Knowledge Security
Protect what AI can expose
02
— Regulatory Change
Keep governance current
03
— AI Cost Management
Make AI spend visible
- TKC — Tacit Knowledge & Context
Data Security Sees the Words Equanimo Understands the Knowledge.
Traditional DLP
Paraphrased knowledge slips through. The exact pattern is gone, so the underlying business context remains invisible.
Equanimo Tacit Knowledge & Context
Tacit Knowledge & Context recognizes that proprietary knowledge is being extracted—even when the wording has been transformed.
- Equanimo
Knowledge Security, Delivered
Knowledge Security Platform
An integrated operating layer for securing enterprise knowledge across AI.
End-to-End Visibility
Observe and govern AI interactions across users, applications, and workflows.
Real-Time Policy Enforcement
Protect sensitive knowledge with continuous monitoring and automated controls.
Always Compliant
Continuously align AI usage with organizational policies and regulatory requirements through audit-ready evidence.
Cost Management
Track and control AI-related costs with clear visibility across users, applications, and workflows.
- Equanimo shield at the center of
Every Governed AI Interaction
01
No workflow changes
02
No Application Modifications
03
Fast, Low-Impact Deployment
01
Protect What Matters Most
02
Use AI with Confidence
03
Control Knowledge Flow
- M2M INTERACTION GOVERNANCE
When AI Calls AI, Governance Follows
- Equanimo
Knowledge Security Meets Enterprise Compliance
GDPR
HIPAA
SOC 2
ISO 42001
EU AI Act
NIST AI RMF
- One operating layer to
Discover, Govern, Protect, and Prove
01
— DISCOVER
See every interaction
- Visibility across web AI tools, APIs, agents, and internal models
- User, team, tool, model, and prompt attribution
- Discover shadow AI and unapproved usage from day one
02
— Govern
Apply policy in real time
- Apply role- and context-aware policies in real time
- Govern approved and unapproved AI usage consistently
- Enforce controls across users, models, agents, and vendors
03
— Protect
Protect Knowledge at Every Interaction
- Detect paraphrased and transformed proprietary knowledge
- Protect prompts, responses, agent interactions, and M2M handoffs
- Block, mask, redact, or control risky knowledge exposure
04
— Prove
Create evidence by default
- Preserve prompts, responses, policy actions, and outcomes
- Maintain searchable evidence across the AI lifecycle
- Support compliance, investigations, audits, and reporting
- Four Security Layers
One Knowledge Security Platform
Knowledge Security requires more than governance—it requires continuous visibility, policy enforcement, knowledge protection, and trusted evidence. Equanimo delivers all four through a unified control plane.
Discover
Continuously discover AI applications, models, agents, users, and enterprise knowledge flowing across your AI ecosystem.
Govern
Apply intelligent policies, guardrails, compliance controls, and vendor governance before knowledge leaves your organization.
Protect
Inspect prompts and responses, classify enterprise knowledge, assess risk, and prevent intellectual property exposure in real time.
Prove
Generate immutable audit trails, compliance evidence, explainability records, and forensic artifacts for every AI interaction.
- BUILT DIFFERENT
Not Another, DLP, SASE or Agent Governance Layer
Traditional security controls data, networks, or agent access. Equanimo goes deeper—governing the knowledge AI can access, transform, and share across every interaction.
| Traditional DLP | SASE | Agent Governance Tools |
Equanimo
|
|
|---|---|---|---|---|
|
What it does
|
Blocks known patterns and sensitive data | Controls where data can flow | Controls where AI agents can operate | Detects knowledge extraction and enforces policy at every hop |
|
What it sees
|
Files, emails and known data patterns | Network traffic, access and destinations | Agent actions, tools and destinations | Knowledge in context across humans, agents and AI |
|
Where it falls short
|
Misses paraphrased or inferred knowledge | Cannot understand what knowledge AI is accessing | Limited visibility into knowledge-level risk and AI-to-AI interactions | Understands meaning, context and intent—not just patterns |
|
Deployment
|
Requires rules, policies and ongoing tuning | Requires network-level configuration | Often requires technical integrations | Zero-code deployment with policies applied in minutes |
- A more useful first conversation
See where your AI governance breaks today — and what it takes to fix it