SOLUTIONS — BY ROLE: ML / LLM ENGINEER
Evaluate Better.
Retrain Faster. Ship Safer.
TestSavant.ai lets you surface real failure modes with Red Teaming and Nero, retrain hardened guardrail models via Auto-tune (Airflow), and enforce safety at runtime through the TestSavant API on Ray. Clean data flows from the Data Synthesizer & Aggregator.
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Higher Eval Coverage
Nero-generated attacks + human packs find issues earlier.
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Faster Hardening Cycles
Auto-tune retrains, validates, redeploys guardrails quickly.
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Cleaner Datasets
Synthesizer & Aggregator fuse traces, synthetics, domain sets.
Engineer Workflow: Eval → Retrain → Enforce
Keep your assistants robust without refactoring your stack.
Evaluation & Red Teaming
- Attack packs: injection, exfiltration, tool misuse, retrieval poisoning, weak citations
- Nero generates novel variants from traces and the Attack Knowledge DB
- Fail gates on criticals; regression suites per release
Auto-tune Retraining (Airflow)
- Ingest findings → retrain guardrails → validate → redeploy
- Optional human sign-off; diffs & metrics archived
- Rapid cadence to keep pace with new attacks
Runtime Guardrails (API on Ray)
- Attach checks to prompts, RAG, and tool calls
- Categories: prompt-injection, toxicity, privacy/PII, tool-safety
- Per-request telemetry feeds the Aggregator
Data Synthesizer & Aggregator
- Fuse telemetry, Red Teaming, Nero, synthetics, domain corpora
- Produce clean datasets for training & evaluation
- Support external sources (papers, HF, CSVs)
Failure Modes → Controls That Hold
Every finding becomes training signal and runtime enforcement.
| Failure Mode | Runtime Guardrail | Test Method | Result |
|---|---|---|---|
| Prompt injection / jailbreak | Block or transform; quarantine artifact | Nero variants + human lure suites | Takeover blocked; evidence logs |
| PII/PHI exfiltration | Detect → mask/tokenize before any external call | Adversarial PII payloads; log path probes | Leakage reduced; masking proofs |
| Retrieval poisoning / weak citations | Require strong provenance; deny low-trust sources | Source-integrity & citation tests | Trustworthy answers; lineage trail |
| Tool/action misuse | Deny/transform risky function calls | Function-call abuse suites | Unsafe actions blocked; audit trail |
| Drift / robustness regressions | Trigger Auto-tune; redeploy hardened guards | Scheduled regression packs; challenger runs | Controlled updates; tracked diffs |
Architecture & Controls
Discover with Red Teaming/Nero → synthesize data → Auto-tune retrain → serve via API on Ray → feed telemetry back.
Guardrail Models (API on Ray)
- Attach to prompts/RAG/tools
- Categories: injection, toxicity, privacy/PII, tool-safety
- Telemetry per request
Red Teaming (Hybrid)
- Automated + manual packs
- Black-box model friendly
- Findings drive retraining
Auto-tune (Airflow)
- Ingest → retrain → validate → redeploy
- Diffs/metrics archived
- Optional human approval
Nero (Autonomous Attacker)
- Self-play; learns from traces
- Generates novel attacks
- Feeds Red Teaming & datasets
Attack Knowledge DB
- Patterns/signatures + examples
- Retrieval memory for Nero
- Continuously updated from research/incidents
Data Synthesizer & Aggregator
- Fuse telemetry, synthetics, domain sets
- Produce clean datasets for training/tests
- Supports external sources (papers, HF, CSVs)
Evidence Support for AI Frameworks
Export artifacts aligned to ISO/IEC 42001, ISO/IEC 23894, NIST AI RMF, GDPR Art 22 / 15(1)(h).
NIST AI RMF 1.0
- ✓Risk registers from attack results, drift, guardrail performance.
ISO/IEC 42001 (AIMS)
- ✓PDCA artifacts: diffs, validations, incident learnings.
ISO/IEC 23894:2023
- ✓Risk lifecycle: identify → analyze → treat → monitor & re-test.
GDPR (Automated Decisions & Rights)
- ✓Explainability excerpts; human-review trails where applicable.
Frequently Asked Questions
Do I need to refactor our LLM stack?
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No. Guardrails attach at the orchestration edge via the TestSavant API. We also support black-box model providers.
Can I run packs locally and in CI?
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Yes. Run Red Teaming packs on demand and as release gates. On criticals, Auto-tune can retrain guardrails and re-validate before promotion.
Engineer Faster, Ship Safer
See the evaluation → retrain → runtime loop working end-to-end.
