Ephiria

Ephiria is a governance and control platform for AI tools, AI agents, and automated processes, built for law firms, in-house legal teams, and other regulated industries. It enforces an organization's policy at the point an action is taken, before that action completes, across three areas: AI tools used by employees, autonomous AI agents, and automated workflows or system-to-system processes. The platform redacts confidential or regulated data before it reaches an AI model, evaluates actions against declared authority and budget limits, and generates a tamper-evident record of what was allowed, blocked, or redacted, and under whose authority.

Key features and functions include:

AI Gateway
Sits between users and the AI tools already in use across an organization, including tools adopted outside of sanctioned channels, applying policy enforcement, cost control, matter context, and output checks at that point of use.

Data redaction
Removes confidential or regulated data before it reaches an AI model and restores it in the returned output. This is carried out by the Secure Interaction Layer (SIL), which mediates each action through five steps, hold, classify, evaluate, condition, and dispose, and can permit, condition, hold, or block an action rather than simply allow or refuse it.

Agent governance
New AI agents and automated workflows are configured with a declared purpose, authority, permitted tools, applicable policy, and budget before deployment; actions outside those parameters are declined by default. The same configuration is enforced again on every call the agent makes at runtime, with actions held or routed for approval when they fall outside it.

Workflow and process governance
Applies the same policy controls to automated workflows, integrations, and system-to-system actions across existing infrastructure, including processes that do not involve AI. Enforcement points are available for AI providers, legal and matter systems, finance and ERP systems, claims and policy systems, identity systems, document systems, workflow systems, and governance, risk, and compliance systems.

Contextual policy evaluation
Establishes who is acting, on whose behalf, over what data, and under what authority within a given matter or workflow, drawing context from the enterprise systems that already hold it rather than from the request alone.

Policy resolution
Resolves applicable policy from four sources, a general baseline, regulatory requirements, client-specific obligations, and the organization's own approved positions, in a fixed order so that the same situation produces a consistent result. Each policy carries a version and effective date and can be tested against historical activity before it takes effect.

Output verification
Checks whether an AI-generated response holds up against applicable policy, regulation, and process before it reaches the user, verifying sources and offering alternatives where a route is blocked. A low-confidence result on a high-consequence action is routed to a person rather than delivered outright.

Cost governance
Checks a forecast cost against the remaining budget for a client, matter, or team before it is committed, and selects the permitted execution path based on capability, cost, latency, and consequence.

Audit trail
Produces a tamper-evident, hash-chained record of permitted, blocked, and redacted actions, written before the outcome takes effect. The record is available in full internally and redacted by default for external use.

Decision graph
Connects each governed decision to the context that produced it and the outcome that followed, applying that history to future cost forecasting, execution routing, and policy tuning.