01
Velocity
AI is outrunning the org chart
Adoption moves faster than security, compliance and IT can track - creating shadow AI, uncontrolled agent behaviour and sensitive-data exposure.
Enterprise AI & Data Trust, Governance & Data Enablement
9jurisdictions100+frameworks0data copies
Enable trusted data.Govern trusted AI.
Prove every decision.
A platform-agnostic trust layer that connects to the data platforms, lakehouses and object stores you already run - unifying AI systems, data assets, policies, identities and events into one continuously monitored control plane.
0/ 1000
Continuous trust score · day 90
9jurisdictions100+frameworks0data copies
How AegisDatastra works
Platform-agnostic·Policy-as-code·Zero-copy governance·Immutable evidence·Continuous trust score·Human oversight·Provable compliance·
Platform-agnostic·Policy-as-code·Zero-copy governance·Immutable evidence·Continuous trust score·Human oversight·Provable compliance·
01The challenge enterprises face
AI adoption alreadyoutran your controls.
04fractures
Four fractures show up in every enterprise we walk into. None of them are solved by another spreadsheet of controls.
02
Method
Static checklists can’t watch runtime
Quarterly GRC spreadsheets cannot keep pace with live model behaviour, agent execution, drift, hallucination, bias and output-level policy violations.
03
Estate
The data estate is in pieces
Records sit fragmented across warehouses, lakehouses, databases and cloud storage - hard to prepare, hard to govern, harder to expose safely to AI.
04
Burden
Proof is now the deliverable
Regulators and enterprise buyers expect deterministic evidence, explainability, human oversight and AI supply-chain assurance - on demand.
Network operationsCybersecurityEnterprise riskPrivacyComplianceInternal auditProcess safetyAsset integrityModel riskThird-party riskFinancial crimeAI initiatives
Collapses into
One continuous enterprise trust layer.
Deployed alongside existing systems. No rip-and-replace. No sensitive data moved to be governed.
02How AegisDatastra works
Six moves, one continuous loop.
01 / 06Find everything
01Find everything
Discover
Every data asset, model, agent and process - inventoried.
Read-only connectors sweep warehouses, lakehouses, databases and object stores to build a living inventory of data assets, AI systems, agents and the business processes they touch. Shadow AI stops being unknown.
- Asset inventory
- Shadow AI discovery
- Lineage graph
- Process registry
02Understand it
Classify
Sensitivity, purpose, quality and obligation - resolved per asset.
Structured, semi-structured and unstructured estates are labelled for sensitivity, residency, purpose and quality, then mapped to the regulatory obligations that actually apply to them.
- Sensitivity labels
- Quality checks
- Residency
- Obligation mapping
03Write it once
Govern
Policy-as-code authored centrally, versioned like software.
Controls are authored once as executable policy - access, purpose, retention, human-approval gates, agent boundaries - then version-pinned so every decision can be replayed against the exact rule that governed it.
- Policy-as-code
- Control library
- Version pinning
- Approval gates
04Serve trusted data
Enable
AI-ready data exposed without copying or centralising it.
Models, agents, notebooks and pipelines are handed governed, compliant, high-quality data in place. Zero-copy by design: governance travels to the data instead of the data travelling to governance.
- AI-ready data
- Zero-copy
- Least privilege
- Purpose binding
05Hold the line
Enforce
Runtime enforcement across access, execution, tools and output.
Every request is evaluated in real time - PII scrub, RBAC, tool allow-lists, behavioural boundaries, output-leak detection - and high-risk decisions escalate to a human before they land.
- Runtime checks
- Agentic guardrails
- Output review
- Escalation
06Show the receipt
Prove
Immutable, hash-linked evidence for every governed action.
Each access request, policy decision, tool invocation, model event, output review and exception lands in an append-only evidence lake - retrievable at regulator request in minutes, not weeks.
- Evidence lake
- Hash chain
- Audit retrieval
- Trust score
Aegis Datastra trusted outcomes
- 01Trusted dataGoverned, classified, AI-ready
- 02Trusted AIRegistered, scored, supervised
- 03Trusted agentsLeast-privilege, bounded, observed
- 04Trusted decisionsEvidenced, explainable, provable
03Unified AI & data trust architecture
Five integrated layers.
One trust score.
01
Data Enablement
Discover, classify, inventory, lineage-track and quality-check trusted, AI-ready data across structured, semi-structured and unstructured estates.
- Inventory
- Classification
- Lineage
- Quality
0layers
0trust score
0copies made
04Your AI & data estate, unified
Define policy once,enforce it everywhere
One authored control travels to Snowflake, Databricks, Azure, BigQuery, MongoDB, Oracle and Postgres - and to every model, agent, notebook, pipeline, task and query that touches them.
policy / pii-boundary.aegis
signedv4.2.0
1# policy/pii-boundary.aegis
2apiVersion: aegisdatastra/v1
3kind: DataAccessPolicy
4metadata:
5name: pii-boundary
6version: 4.2.0
7obligations: [GDPR.Art9, HIPAA.164.312, EU-AI-Act.Art14]
8scope:
9estate: [snowflake, databricks, bigquery, postgres]
10movement: zero-copy
11enforce:
12models: redact(pii) · purpose_bind · log(evidence)
13agents: least_privilege · tool_allowlist · boundary
14notebooks: sample_only · no_export
15pipelines: lineage_required · quality_gate
16tasks: owner_required · evidence_ttl(30d)
17review:
18output: [drift, bias, hallucination, leak]
19human_gate: confidence < 0.75
20evidence: append_only · hash_chain · immutable
Zero-copy · governed in place0 / 8 surfaces enforced
Committed toSnowflakeDatabricksAzureAWSBigQueryMongoDBOraclePostgres
Enforcement surfaces
- Models2,624enforced
- Agents418enforced
- Notebooks1,109enforced
- Pipelines3,540enforced
- Tasks12.4kenforced
- Queries· liveenforced
- Outputs· liveenforced
- Approval gates· liveenforced
New regulations arrive as executable governance policies - not as a manual procedure circulated to eleven teams.
05Security and control assurance
Controlled autonomy.Provable trust.
Every request carries a confidence. That number decides whether it commits, gets re-derived by a stronger model, or waits for a named human - and the choice itself becomes evidence.
Decision confidence
0.96auto-cycling
Routed toAutomated execution
0.96
0.400.750.901.00
High confidence
Automated execution
Committed straight through, with evidence written by default.
Escalation ladder
- 01Lightweight enginecleared
Routine, low-risk work resolves on small models. Cheap, fast, fully logged.
- 02Process controlsPolicy-checked
Business-process controls and enterprise policy evaluate the request in flight.
- 03Compliance & riskdormant
Regulated decisions escalate through sector compliance, risk and audit controls.
- 04AI governance & trustdormant
The highest-risk decisions require human approval before any action is committed.
Routine operations run on lightweight engines. Higher-risk decisions escalate through progressively stronger controls and human approval.
What holds the boundary
- 01
Controlled agent autonomy
Governs what an agent can do, which tools it can invoke, what data it can reach, and when a human must approve.
- 02
Contextual identity & permissions
Every governed action is tied to identity, role, purpose and source system - no anonymous machine access.
- 03
Deterministic evidence & lineage
Every finding links back to raw evidence, source data and the exact policy version in force at the time.
- 04
Safe AI outputs
Reviews model outputs for drift, bias, hallucination and policy violation before they reach a decision.
- 05
Supply-chain aware architecture
Controlled model orchestration with SLM-first, LLM-following patterns for resilient, cost-aware workflows.
06Immutable evidence lake
Every decision leavesa receipt you canhand to a regulator.
Chain verified
Access requests, policy decisions, tool invocations, model events, output reviews and exceptions land in an append-only lake - each entry hash-linked to the one before it and to the policy version that governed it.
evidence.lake / tail --followappend-only
timeactoractiontargetpolicyverdict
09:41:07agent://underwriting-07READsnowflake.risk.exposurespii-boundary@4.2.0redact
prevbe50f29436d8→29436d87a1cb
09:41:13model://claims-triageINFERdatabricks.claims.goldclinical-safety@2.8.1allow
prev29436d87a1cb→36d87a1cbe50
09:41:19user://a.rahmanEXPORTbigquery.customer.piiresidency-lock@1.4.0deny
prev36d87a1cbe50→9436d87a1cbe
09:41:25agent://pipeline-sentinelTOOLtool://ledger.writeagentic-bounds@3.0.2allow
prev9436d87a1cbe→36d87a1cbe50
09:41:31model://fraud-scoringDECIDEtxn://8841-2207sr-11-7@5.1.0escalate
prev36d87a1cbe50→87a1cbe50f29
09:41:37agent://maintenance-copilotREADhistorian.asset.integrityprocess-safety@2.2.4allow
prev87a1cbe50f29→29436d87a1cb
09:41:43model://care-summaryOUTPUTreview://hallucinationoutput-review@1.9.7escalate
prev29436d87a1cb→436d87a1cbe5
seq 0 · immutable0 mutations
Manual evidence cycle
21 days→0min
Regulator-grade retrieval, on request.
Findings linked to raw evidence
Reconstructed→0%
Source data plus the policy version in force.
Penalty exposure avoided
Unquantified→$0.0M
Cumulative, first 90 days.
07Jurisdictional governance map
Governance that conformswherever you operate.
Nine jurisdictions of enforceable statute, mapped to the obligations that apply to your processes - not a generic checklist of everything a regulator has ever published.
Auto-cycling · move across to steer
Enforceable statute01 / 9
HIPAASOXOCCFFIECOSHA PSMEPAPHMSAFCCState privacy
Frameworks continuously monitored
0instruments shown0controls mapped
EU AI ActNIST AI RMFISO 42001ISO 27001SOC 2GDPRHIPAAHITECHHITRUST CSFNIST CSF 2.0Basel IIIBasel IVSR 11-7CCAROCCFFIECDORAPSD2PCI DSSSWIFT CSPMAS FEATMAS TRMAPRA CPS 234OSFI B-13NIS2EHDSMDR / IVDRISO 27799ISO 27701NIST SP 800-66 r2NIST SP 800-53OSHA PSM 1910.119EPAPHMSAIEC 62443ISO 55001ISO 14224ISO 31000ISO 45001ISO 14001ISO 22301ISO 39001API standardsIMOICAOIATAFAAFMCSAEASAITU-TGSMA Security3GPPETSICSA CCMJoint CommissionNCQA HPAURAC HUMLGPDDPDP ActCorporate policies
08Executive KPI trajectory
Ninety days fromreactive to continuous.
Direction of travel under continuous governance. These are the lines the board asks about - and the ones a regulator can now be shown on request.
21 days
14 min
Manual evidence cycle becomes regulator-grade retrieval
0
862 / 1000
Continuous trust score by day 90, up from nothing
Unknown
$23.7M
Cumulative penalty exposure avoided in 90 days
Day 1
Day 90
Governance
Policy compliance
74%→98%
Audit evidence retrieval
3 wks→< 10 min
Manual compliance reviews
68%→< 15%
Regulatory readiness
Reactive→Continuous
Operations
Model approval cycle
21 days→48 hrs
Executive risk visibility
Quarterly→Continuous
Control effectiveness
48%→94%
AI Trust
AI systems governed
22→Enterprise-wide
Shadow AI discovery
Unknown→100%
Human oversight coverage
38%→100%
Board dashboard · continuous director visibility11 oversight domains
- 01Enterprise governancelive
- 02Business process healthlive
- 03Internal controlslive
- 04Risk exposurelive
- 05Regulatory compliancelive
- 06Audit readinesslive
- 07Operational resiliencelive
- 08Cybersecurity & OT risklive
- 09Third-party risklive
- 10AI governancelive
- 11Executive trust scorelive
09Built for regulated industries
Same trust layer.Your regulator’s language.
Banking, energy, healthcare, telecom and transportation each arrive with their own statute set, their own board questions and their own definition of unacceptable risk. The control plane does not change - the obligations mapped into it do.
Banking & Financial Services
“How do we modernise banking with AI, continuously demonstrate compliance with Basel, SR 11-7, DORA, PCI DSS, GDPR, the EU AI Act, OCC and FFIEC - and still operate at the speed of modern finance?”
What we govern here- Model risk management
- Financial crime controls
- Internal audit
- Third-party & resilience
- Agentic AI governance
80+
Banking regulations1,000s
Enterprise controls100s
Business processesModel approval cycle
Statutes & frameworks mapped21 days → 48 hrs
Basel III / IVSR 11-7CCAROCCFFIECDORAPSD2PCI DSSSWIFT CSPMAS FEATRBIAPRA CPS 234
Auto-advancing · select a vertical to pin it
10What makes AegisDatastra different
01
Platform-agnostic by design
Deployed alongside the stack you already run. No rip-and-replace, no migration project, no vendor lock.
02
AI-native governance
Built for model behaviour, agent execution and output-level policy - not a GRC checklist retrofitted for AI.
03
Zero-copy trust layer
Governance travels to the data. Sensitive records never leave the system of record to be governed.
04
Continuous trust score
One executive number, continuously recomputed from live control effectiveness and evidence freshness.
05
Provable compliance
Deterministic, hash-linked evidence produced by default - auditable at regulator request, not reconstructed.
Trust platform capabilities · already shipped14 modules
- Business Process Registry
- Process-Control Mapping
- Enterprise Control Library
- Policy-as-Code
- Regulatory Obligation Mgmt
- Internal Audit Automation
- Enterprise Risk Register
- Cybersecurity Governance
- AI Registry
- Agentic AI Guardrails
- Continuous Trust Score
- Immutable Evidence Lake
- Audit Retrieval Engine
- Executive Board Dashboard
Works with the stack you already have - read-only, zero-copy
Snowflake+Databricks+Azure+AWS+BigQuery+MongoDB+Oracle+Postgres+
Let’s begin
Let’s make your AIprovable, explainable,compliant and audit-ready.
Platform-agnosticPolicy-as-codeZero-copy governance
Govern the Enterprise. Trust the AI. Prove the Compliance.