Foundation
ExploreAutomatic Ontologies
Turning policies, SOPs, API schemas, workflow logs, and evaluated agent traces into explicit, versioned rule layers.
Research
The technical foundation behind evidence-aware write safety.
Rippletide started as deep research and still runs on it. Hypergraph decision databases, automatic ontologies, and neuro-symbolic reasoning power the Action Runtime: applying business rules to current facts before agent actions take effect.
Long-term direction
Runtime Reinforcement
Rippletide's long-term product direction is Runtime Reinforcement: using guarded actions, approvals, blocks, corrections, and traces to suggest stronger explicit policies over time. Enforcement remains deterministic, auditable, and human-governed: the system proposes guard improvements and regression scenarios, humans accept, edit, or reject them.
- Deterministic rule evaluation, not probabilistic generation
- Every decision traceable to data, rule, outcome, and reason
- Guard improvements proposed by the system, approved by humans
Foundation
ExploreContext Graph for Agents
The hypergraph decision database that combines memory (facts, context, provenance) with reasoning (plans, rules, constraints).
Foundation
ExploreAI Agent Production Readiness Test
Evaluating agent behavior against ground-truth outcomes, the discipline underneath unsafe scenario testing.
Deep explainers
The thinking, page by page
Long-form technical pages written along the research. They use the research vocabulary and go deeper than the product pages.
Also see The Decision Layer podcast.
- Agent Decision Infrastructure: Why agent actions need a decision layer between proposal and execution.
- AI Agent Auditability: What a causal decision trace must contain to satisfy a review.
- AI Agent Governance: The governance questions enterprises ask before agents act.
- AI Agent Reliability: Why task accuracy alone does not make an agent production-safe.
- Monitoring vs Pre-Execution Enforcement: The difference between observing failures and preventing them.
- Guardrails vs Decision Runtime: Where prompt guardrails stop and action-level decisions begin.
Looking for the product?
The Action Runtime applies business rules to agent actions in production. Reduce Human Review is a way to start: evaluate one important action in a 10-Day Proof without changing production. Production activation is scoped separately.