Feature

Enterprise AI
observability.

See how AI is used across your organization, find recurring workflow friction and unusual activity, and open the sessions that explain every finding.

Enterprise layer

Turn AI activity into evidence your team can act on.

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Unified activity visibility

See AI work captured from native agent hooks, browser conversations, local proxy traffic, and the enterprise gateway in one organization view.

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Attributable token usage

Connect usage to the team, project, developer, model, provider, and capture source that produced it—not just a provider total.

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Workflow Signals

Find recurring patterns such as restart churn, repeated file discovery, context bloat, duplicated work, policy drift, and model–task mismatch.

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Deterministic anomaly review

Review unusual usage, first-seen technology, and runaway sessions with severity, status, occurrence history, and linked evidence.

Evidence chain

Follow every finding back to the work that produced it.

Aggregate dashboards can show where usage changed. ReclaimLLM preserves the organization, team, project, member, model, provider, and capture source behind it.

Signals and anomaly reports add an investigation path: see what matched, inspect the evidence sessions, and decide what needs enablement, policy, or no action.

Organization viewUsage attributed across members, teams, projects, models, providers, and capture sources
Signals matrixRecurring workflow patterns grouped by team and project, ranked by projected tokens or open count
Anomaly reportsNightly deterministic checks with detector, severity, status, subject, and occurrence history
Evidence sessionsThe prompts, responses, tool activity, and file changes behind a signal or anomaly when captured

Differentiation

Built for investigation, not employee surveillance.

Observe the workflow, not one provider

ReclaimLLM normalizes sessions from coding agents, browser assistants, API proxy traffic, and the enterprise gateway so teams can investigate AI work across their actual tool stack.

Find repeatable operational waste

Signals surface patterns that aggregate charts miss: repeated restarts, redundant discovery, oversized context, duplicated work, onboarding gaps, and avoidable model cost.

Keep findings explainable

Deterministic detectors state what matched and how to interpret it. Admins can open the linked sessions before acknowledging, resolving, dismissing, or routing a fix.

Workflow

From captured activity to accountable action.

01

Capture

Normalize sessions from native hooks, browser conversations, local proxy traffic, and the enterprise gateway.

02

Attribute

Connect activity to the organization, team, developer, project, model, provider, and capture source.

03

Detect

Surface recurring workflow Signals and deterministic anomalies from completed session evidence.

04

Act

Open the evidence, choose the right owner, and acknowledge, resolve, dismiss, or route the finding.

Investigation coverage

Find the patterns that rollup dashboards hide.

The Signals matrix groups recurring AI-work patterns by team and project, showing projected weekly tokens when available and open finding count when not.

Anomaly reports run deterministic nightly checks for unusual usage, new technology fingerprints, and runaway sessions—with interpretation guardrails for every detector.

Usage deviationCompare each member's session and token volume with their own rolling history
Runaway sessionsFind identical retries, repeated failures, abnormal tool-call volume, and unusually long runs
Technology noveltyReview first-seen combinations of dependencies, imports, manifests, tools, and project activity
Workflow frictionLocate restart churn, repeated file discovery, exploration without landing, and session idle gaps
Efficiency gapsSurface context bloat, onboarding cost, duplicated work, and model–task mismatch
Admin reportingFilter by date, detector, severity, and status; review evidence; export the monthly Signals CSV

Make every AI operations finding explainable.

Connect organization-wide usage to recurring workflow Signals, deterministic anomalies, and the exact sessions your admins need to review.