AI Red Teaming & LLM Pen Testing
Find weaknesses before attackers do.
- Prompt-injection and jailbreak testing
- Data-leakage and exfiltration tests
- Agent tool-abuse scenarios
- Detailed findings and fixes
AI Governance and Security Services for Safe, Compliant AI at Scale
We help you test, secure and govern AI systems from red-teaming LLM applications and adding guardrails to building AI policies, risk registers and compliance evidence for regulators, auditors and customers.
- AI Red Teaming
- LLM Guardrails
- AI Risk Assessment
- Regulatory Readiness
prompt-firewall ● LIVE
- [BLOCK] prompt injection → stopped by Guardrails
- [PASS] customer query → answered, cited, logged
- [BLOCK] tool abuse → denied by Policy
- [PASS] HR policy question → answered, logged
AI Moves Fast. Risk Moves Faster.
Generative AI and agents introduce new risks: prompt injection, data leakage, hallucinated advice, biased decisions and agents taking unintended actions. At the same time, regulations and customer expectations around AI are tightening.
AI Technocrats provides AI governance services that combine security engineering with practical policy work. We test your AI systems the way attackers and real users would, fix what we find with guardrails and architecture changes, and set up the governance processes that keep AI safe as it evolves.
Because we build AI systems ourselves, our recommendations are concrete specific controls, code-level fixes and monitoring not just checklists.
Our Capabilities
AI Governance & Security Services
Protect your users, data and reputation as you scale AI.
Guardrails Implementation
Add runtime protection to AI apps.
- Input and output content filters
- PII detection and redaction
- Topic and action restrictions
- Grounding and citation checks
AI Evaluation & Monitoring
Measure quality and safety continuously.
- Hallucination and accuracy benchmarks
- Bias and fairness testing
- Drift and performance monitoring
- Incident alerting
AI Policy & Governance Framework
Set clear rules for AI use.
- Acceptable-use and GenAI policies
- AI system inventory and risk register
- Approval workflows for new AI
- Roles and accountability (RACI)
Regulatory & Standards Readiness
Prepare for audits and regulation.
- EU AI Act risk classification
- India DPDP Act data-handling review
- ISO/IEC 42001 gap assessment
- NIST AI RMF alignment
Secure AI Architecture
Design AI systems that are safe by default.
- Least-privilege agent design
- Private and on-premise LLM options
- Secrets and key management
- Tenant and data isolation
Why AI Governance Matters Now
AI governance is the set of policies, processes and technical controls that ensure AI systems are safe, fair, secure and compliant throughout their lifecycle. It covers which AI is allowed, how it is tested, who approves it, how it is monitored and how incidents are handled.
Large language models need new security practices. A model can be tricked by instructions hidden in a web page or document (prompt injection), reveal confidential data from its context, or when connected to tools take actions nobody intended. Traditional application security testing does not catch these issues on its own.
Our AI governance services join the two worlds: technical testing and guardrails for each AI system, and an organisation-wide framework that maps to standards such as ISO/IEC 42001 and the NIST AI Risk Management Framework, and to regulations including the EU AI Act and India's DPDP Act.
Traditional App Security vs LLM Security
A side-by-side view of what changes.
| Concern | Traditional application security | LLM and agent security |
|---|---|---|
| Main attack surface | Code, APIs and infrastructure | Prompts, retrieved content and tools |
| Typical threats | Injection, auth flaws, misconfiguration | Prompt injection, data leakage, tool abuse |
| Testing method | Pen testing and code scanning | Adversarial red teaming and evaluations |
| Behaviour | Deterministic | Probabilistic, needs continuous evaluation |
| Controls | WAF, access control, patching | Guardrails, output validation, least-privilege tools |
Benefits of Strong AI Governance
What a mature governance programme gives you.
01
Fewer AI incidents
Vulnerabilities are found and fixed before launch.
02
Faster approvals
Clear processes let teams ship AI with confidence.
03
Regulatory readiness
Documentation and evidence ready for audits.
04
Customer trust
Demonstrable controls win enterprise deals.
05
Data protection
Sensitive information stays where it belongs.
06
Consistent quality
Continuous evaluation keeps AI accurate over time.
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Custom AI solutions designed to empower your business growth.
How It Works
Our AI Assurance Lifecycle
A continuous loop that keeps every AI system safe after go-live.
-
01
Inventory
Catalogue AI systems, models, data and owners.
-
02
Assess
Classify risk and review architecture and data flows.
-
03
Test
Red-team and evaluate for security, safety and accuracy.
-
04
Protect
Implement guardrails, controls and fixes.
-
05
Monitor
Track behaviour, incidents and compliance evidence.
AI Governance by Industry
Controls tailored to sector-specific risk and regulation.
BFSI
- Model-risk management for AI
- Explainability for credit decisions
- Customer-data protection
- Conversational-AI compliance
Healthcare
- Clinical-safety evaluation
- Patient-data privacy
- Bias testing
- Human oversight design
Government & PSUs
- Sovereign-data controls
- Citizen-facing AI safety
- Procurement AI checklists
- Audit-ready documentation
SaaS & Technology
- Customer-facing LLM security
- Multi-tenant data isolation
- Security questionnaires for AI
- Trust-centre content
Manufacturing
- Safety-critical AI validation
- Edge-model integrity
- OT-network isolation
- Change control for models
HR & Education
- Fairness in screening and grading
- Transparency notices
- Consent management
- Appeal processes
Engagement
Our AI Governance Engagement
-
01
scopingScoping ✔ doneWe agree which AI systems, regulations and risks are in scope.
-
02
discovery --inventoryDiscovery & Inventory ✔ doneWe map AI use, data flows, vendors and owners.
-
03
test --assessTesting & Assessment ✔ doneWe red-team systems and assess controls against frameworks.
-
04
remediateRemediation ✔ doneWe implement guardrails and fix architecture and policy gaps.
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05
rollout --trainFramework & Training ✔ doneWe roll out policies, processes and team training.
-
06
assure --continuousContinuous Assurance ✔ doneWe provide monitoring, periodic re-testing and reporting.
AI Security & Governance Toolkit
Frameworks
- NIST AI RMF
- ISO/IEC 42001
- OWASP Top 10 for LLMs
- MITRE ATLAS
Regulations
- EU AI Act
- India DPDP Act
- Sector regulator guidelines
Testing Tools
- Garak
- PyRIT
- Promptfoo
- Custom attack suites
Guardrails
- NeMo Guardrails
- Guardrails AI
- Llama Guard
- Presidio
Evaluation & Monitoring
- DeepEval
- RAGAS
- Langfuse
- Arize Phoenix
Security Infrastructure
- SSO / RBAC
- Vault
- SIEM integration
- Audit logging
Trending Now
AI Governance Trends to Watch
The shifts shaping how organisations invest in this area.
ComplianceALERT_01
Regulation coming into force
Obligations under laws such as the EU AI Act are phasing in, raising documentation expectations.
SecurityALERT_02
Agent security
AI agents with tool access create new risks that need least-privilege design and monitoring.
StandardsALERT_03
AI management systems
ISO/IEC 42001 is giving organisations a certifiable structure for AI governance.
QualityALERT_04
Continuous evaluation
Automated tests for safety and accuracy now run on every model or prompt change.
Why Choose AI Technocrats for AI Governance
Builders turned testers
We know how AI systems fail because we build them.
Fixes, not just findings
We implement the controls we recommend.
Framework fluency
Mapped to ISO 42001, NIST AI RMF and regulations.
India and global
DPDP Act and EU AI Act considerations covered.
FAQ
AI Governance & Security: Frequently Asked Questions
Can't find what you're looking for? Talk to our AI specialists.
What are AI governance services?
AI governance services help organisations manage AI responsibly through policies, risk assessments, testing, guardrails, monitoring and documentation, so AI systems are safe, fair, secure and compliant.
What is AI red teaming?
AI red teaming is adversarial testing of AI systems. Testers try prompt injection, jailbreaks, data extraction and misuse of connected tools to find weaknesses, then recommend fixes.
What is prompt injection?
Prompt injection is an attack where malicious instructions are hidden in user input or in content the AI reads, such as web pages or documents, to make the model ignore its rules or leak data. It is one of the top risks for LLM applications.
Does the EU AI Act apply to Indian companies?
It can. Companies outside the EU may be affected if they place AI systems on the EU market or their AI outputs are used in the EU. We help assess applicability and risk classification; for legal advice, consult qualified counsel.
How does India's DPDP Act affect AI projects?
AI systems that process personal data must follow the DPDP Act's requirements on consent, purpose limitation and data protection. We review data flows in AI systems and recommend controls; this is not legal advice.
Can you add guardrails to an AI app we already built?
Yes. We assess the existing application, then add input and output filtering, PII redaction, permission checks and monitoring with minimal changes to your code.
How often should AI systems be red-teamed?
Before launch, after significant changes such as new models, tools or data sources, and periodically in production. Continuous automated evaluation complements periodic manual testing.
What is ISO/IEC 42001?
ISO/IEC 42001 is an international standard for AI management systems. It sets requirements for governing AI responsibly across policies, risk management, lifecycle controls and continual improvement.
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