Solutions
Governance, accountability, and audit for any AI system. Select a solution to learn more.
Multi-Agent Systems with Restricted Information
When multiple agents collaborate but some information is restricted
The Challenge
- • Multiple agents collaborate (retrieval, tool, planner). Some sources are restricted, including PII or internal documents.
- • Only specific agents or memory scopes can access certain information. Must prove compliance.
Why Current Solutions Fail
Permissions exist at the app layer, but memory is a shared blob. Once information enters context, there's no way to prove it was "forgotten" after use.
How Synaptik Solves It
- ✓ Memory-level access control with cryptographic proofs
- ✓ Tamper-proof audit trail of which agents accessed what
- ✓ Provably deleted information with crypto-shred guarantees
ML Workflow Provenance and Reproducibility
Track exactly what data, features, and configurations produced each artifact
The Challenge
- • A team trains and ships models regularly. They need to answer exactly what data, features, and configurations produced a specific artifact.
- • Must know what changed since the previous run and what human overrides were applied.
Why Current Solutions Fail
ML tooling tracks artifacts, but decision state lives across scattered logs, notebooks, and tickets. Reproducibility is manual. No unified, enforceable memory.
How Synaptik Solves It
- ✓ Unified memory of all decisions, data, and configurations
- ✓ Content-addressed snapshots for perfect reproducibility
- ✓ Human overrides tracked with cryptographic signatures
Regulated AI Decision Workflows
Prove compliance for AI-assisted approvals and decisions
The Challenge
- • Enterprise runs AI-assisted workflows for approvals: refunds, claims, clinical coding, vendor access.
- • System must remember prior interactions, policy changes, and exceptions, and prove what it relied on for each decision.
Why Current Solutions Fail
Current stacks reconstruct context after the fact, but can't prove restricted data wasn't used or that policy constraints were applied at runtime.
How Synaptik Solves It
- ✓ Policy gates enforce restrictions at admission time
- ✓ Cryptographic audit trail proves what was used for each decision
- ✓ Regulatory-ready evidence packs for compliance audits
RAG Systems with Document-Level Access Control
Prove which documents influenced answers and prevent leakage
The Challenge
- • RAG over internal documents where some are confidential, some public, some require specific clearance.
- • Prove which documents influenced an answer and that restricted ones weren't used without authorization.
Why Current Solutions Fail
Retrieval logs show what was fetched, but context is merged before generation. No proof restricted content didn't leak into the response.
How Synaptik Solves It
- ✓ Document-level provenance with cryptographic lineage
- ✓ Access control enforced at memory admission
- ✓ Audit trail proves which documents influenced each response
Chained Model Pipelines with Silent Failures
Identify exactly which model introduced errors or drift
The Challenge
- • Pipeline chains models: classifier → extractor → summarizer → generator. Output is wrong.
- • Must identify exactly which model introduced the error or drift.
Why Current Solutions Fail
Each model logs independently. No unified trace across the chain. Failures appear at the end with no upstream visibility.
How Synaptik Solves It
- ✓ Unified trace across the entire model pipeline
- ✓ Stage-by-stage telemetry tracks errors at origin
- ✓ Drift detection with cryptographic baselines
Agentic Systems Taking Irreversible Actions
Verify authorization before execution and prove intent
The Challenge
- • Agent can call APIs, write to databases, send emails, execute transactions.
- • Before each action executes, verify it's authorized and log why it was taken.
Why Current Solutions Fail
Guardrails often run post-hoc or in parallel. Action may execute before policy check completes. Can't prove intent was gated before execution.
How Synaptik Solves It
- ✓ Pre-execution policy gates block unauthorized actions
- ✓ Intent tracking with cryptographic proofs
- ✓ Audit trail proves authorization preceded execution
Why Synaptik?
Synaptik sits outside the model as a governance layer. It enforces policy at admission, creates tamper-proof audit trails, and preserves memory with provenance.
Without this layer, AI systems rely on logs and prompts after the fact. With it, you get enforceable guarantees at decision time.