01
AI TEVV
Testing, Evaluation, Verification & Validation
Evaluate behavior against requirements, mission objectives, criteria, and intended use.
- Requirements-based evaluation
- Benchmarks and acceptance thresholds
- Reproducible technical evidence
Government AI assurance
Who independently validated your AI?
Vendors build AI. Integrators deploy AI. BlackIndian AI independently validates it.
Independent testing, evaluation, adversarial assessment, validation, and continuous monitoring before and after deployment.
Explore our Assurance Lab →The independent assurance layer
From implementation to independent evidence.
01
AI VENDOR
Builds AI
02
SYSTEMS INTEGRATOR
Integrates + deploys
03
BLACKINDIAN AI
Tests + attacks + validates + monitors
04
AGENCY
Receives independent evidence
The organization that builds an AI system should not necessarily be the only organization evaluating whether it performs as required. We work with integrators rather than replacing them.
Government capabilities
A technical assurance workstream.
02
AI RED TEAMING
Adversarial assessment
Identify vulnerabilities and unintended behavior through controlled adversarial testing.
- Prompt injection
- Jailbreak testing
- Sensitive-data exposure
- RAG manipulation
- System-prompt extraction
03
LLM SECURITY TESTING
Security-focused evaluation
Security evaluation for generative AI and large language model applications.
- LLM applications
- RAG systems
- AI assistants
- Model APIs
- AI workflows
04
AGENTIC AI SECURITY
Action-aware testing
Test systems capable of taking actions, with particular attention to permission boundaries.
- Tool permissions
- Authorization boundaries
- Memory attacks
- Unauthorized actions
- Human approval boundaries
05
AI OBSERVABILITY
After deployment
Evaluate AI behavior after deployment through tracing, telemetry, and regression signals.
- LLM and agent tracing
- Security events
- Evaluation metrics
- Drift and regression
06
CONTINUOUS AI ASSURANCE
Assurance that continues
Keep assurance current as models, tools, prompts, and workflows change.
- Scheduled evaluations
- Model-change testing
- Remediation verification
- Periodic red teaming
BIA-AF™ methodology
From AI system to defensible evidence.
DISCOVER → BASELINE → ATTACK → VALIDATE → OBSERVE → EVIDENCE
DISCOVER→BASELINE→ATTACK→VALIDATE→OBSERVE→EVIDENCE
01DISCOVER
Understand architecture, models, data, APIs, agents, users, requirements, mission, and failure consequences.
02BASELINE
Establish measurable expectations, datasets, metrics, benchmarks, and acceptance thresholds.
03ATTACK
Conduct adversarial testing against models, applications, RAG systems, APIs, and agents.
04VALIDATE
Compare expected behavior with observed behavior and documented requirements.
05OBSERVE
Assess monitoring, tracing, regression detection, telemetry, and continuous evaluation.
06EVIDENCE
Produce reproducible findings and technical evidence stakeholders can evaluate.
What the agency receives
AI assurance evidence package.
Evidence, not merely consulting advice: artifacts stakeholders can inspect, challenge, and use in a decision.
/01Executive AI Assurance Report
/02Technical Assessment Report
/03AI System Risk Register
/04Threat Model
/05Evaluation Dataset & Test Suite
/06Red-team test results
/07Agent security findings
/08RAG security findings
/09API and trace evidence
/10Remediation recommendations
/11Retest results
/12Framework mapping
/13Continuous monitoring plan
/14Final assurance summary
Technical finding format
Make the risk legible.
Illustrative finding format
NOT AN ACTUAL RESULTBIA-AI-001 · Indirect Prompt Injection
Severity
Critical / High / Medium / Low
Status
Open / Remediated / Retest Required / Closed
Evidence
Reproducible technical evidence.
Impact
Potential operational or security consequence.
Reproduction
Steps required to reproduce observed behavior.
Recommendation
Technical remediation guidance.
Retest: PASS / FAIL — populated only after an approved test is executed.
Framework alignment
Recognized practices, accurately described.
Our work may be aligned with, mapped to, or informed by applicable frameworks. Alignment is not certification or government approval.
Aligned with / mapped to / informed by
NIST AI Risk Management Framework
Aligned with / mapped to / informed by
NIST Generative AI Profile
Aligned with / mapped to / informed by
NIST AI TEVV resources
Aligned with / mapped to / informed by
GAO AI Accountability Framework
Aligned with / mapped to / informed by
Applicable OWASP LLM and agent security guidance
Aligned with / mapped to / informed by
Customer-specific security and assurance requirements
Prime contractors & systems integrators
You build it.
We validate it.
BlackIndian AI can provide an independent AI assurance workstream within larger government technology, modernization, cloud, cybersecurity, and AI programs.
Independent workstream
- AI TEVV
- AI Red Teaming
- LLM Evaluation
- Agent Security
- Adversarial Testing
- AI Observability
- Independent Validation
- Continuous Assurance
Procurement information
- Legal business name
- BLACKINDIAN AI
- Website
- blackindianai.com
- Operating entity
- The Gaddis Randolph Group LLC
- Contact
- hello@blackindianai.com
UEI, CAGE, SAM status, NAICS, PSC, business size, certifications, and other identifiers are not displayed until verified.
Next step
Before AI becomes operational, test the assumptions.
Talk with BlackIndian AI about independent testing, adversarial evaluation, validation, and continuous assurance.