Traceability
Know which data sources were consulted, which prompts were answered, which tools were called, and which outputs were shown to users.
EU AI Act · Governed AI infrastructure
Don’t get fined for AI you can’t govern.
If your AI can’t be explained, constrained, and audited, it can become a fine—not a feature. Katara gives teams the controls to keep models, tools, and memory inside policy before the risk becomes regulatory.
Aug 2026EU AI Act enforcement window for high-risk systems is no longer theoretical.
TraceableProve what the model saw, what it used, and what it returned.
AuditableKeep a durable record of every policy check and tool action.
Human-ledAutomation assists the workflow; humans retain the decisions that matter.
01 // Why this matters now
Katara helps you prove control, not just claim it.
If you deploy AI in a high-risk context, the EU AI Act asks for traceability, auditability, and governance. Katara builds those controls into the workflow so policy, logging, boundaries, and accountability are enforced where the work happens.
Auditability
Produce a tamper-evident record of policy checks, approvals, escalations, and human interventions for internal reviews and regulators.
Governance
Apply controls at the layer where AI is actually used, not after the fact—across apps, models, tools, and stored context.
02 // The problem
AI sprawl creates blind spots.
Teams adopt multiple models, copilots, plugins, and agents faster than policy can keep up. The result is familiar: no clear ownership, no complete activity trail, and no reliable answer when someone asks how a decision was made.
Disconnected tools
Different teams connect to different models and services with inconsistent permissions, budgets, and oversight.
Unscoped data access
Without a governed retrieval layer, assistants can surface the wrong content or cross boundaries that compliance never approved.
Missing evidence
When an audit or investigation happens, there is often no replayable record of the request, the source, the policy, or the action taken.
03 // The control plane
Connect, control, and operate every AI workflow.
Katara is built around a simple governance pattern: connect AI to approved knowledge and systems, control what it is allowed to do, then operate with full visibility into the actions it takes.
Connect
Ground responses in the AI Knowledge Base and approved sources. Scope every retrieval path so the assistant only sees what policy allows.
Katara governance layer
POLICY ENFORCED
AUDIT LOGGED
HUMAN REVIEWED
AUDIT LOGGED
HUMAN REVIEWED
Control
Route model traffic through the AI Gateway, restrict available tools via the MCP Registry, and keep memory reuse inside retention rules.
Operate with evidence
Capture what was asked, what the system retrieved, which action was approved, and what the user saw. Make replay and review practical.
Preserve human authority
Katara supports automation, but it does not remove accountability. The system highlights risks and recommendations; humans make the final call.
04 // What compliance teams need
Katara’s solutions map to the questions compliance teams answer.
Instead of treating compliance as a report at the end, Katara makes governance part of the execution path. That way, evidence is captured at the moment of action.
AI Knowledge Base
- ●Keep retrieval inside approved sources and document libraries.
- ●Reduce hallucinations by grounding answers in trusted context.
- ●Control what content can be surfaced to each workflow.
AI Gateway
- ●Apply access checks, policy rules, and usage limits before a request reaches a model.
- ●Route sensitive workloads to approved environments and preferred model classes.
- ●Keep a consistent control point across tools and applications.
MCP Registry
- ●Expose only approved tools, APIs, and actions to agents.
05 // What you can show
The evidence trail is the product.
When teams need to defend an AI-enabled process, they typically need to answer four questions: what happened, why it happened, who approved it, and what the system knew at the time. Katara is designed to preserve those answers by default.
Who asked
Record the user, role, workspace, and request context that started the interaction.
What the system used
Log sources, prompts, retrieved artifacts, model selections, and tool calls associated with the response.
What was allowed
Capture policies applied, boundaries enforced, and the human decision where review was required.
06 // Next step
Ready to make Katara the layer that keeps your AI compliant?
Start with one use case, one team, and one policy boundary. Katara can help you stand up a governed AI pattern that is easier to audit, easier to defend, and easier to scale.
Talk to Katara
Share the workflow you want to govern, and we’ll come back with a scoped path for bringing it under control.
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