Governance
Different metrics need different rigor. ClariLayer enforces tier-based governance — move fast for experiments, move with rigor for the board. AI agents know not just what a metric means, but whether to trust it.
Request Early AccessTwo VPs bring two different numbers for the same metric. The meeting derails from strategy into “auditing the slide.” Once trust breaks, executives revert to gut-feel — the million-dollar data stack becomes useless.
Different departments have legitimate reasons for different views. The problem is not disagreement — it is invisible, ungoverned disagreement. ClariLayer makes variants transparent, intentional, and safe.
Not every metric needs the same rigor. ClariLayer enforces the right level of governance for the right level of stakes.
Tier 0
Any user can define. Self-serve release. Fast-track for internal experiments and exploratory analysis. AI-generated SQL accepted with standard validation.
Tier 1
Any user can define. Owner approval required before release. AI-generated SQL requires a validation pass plus owner sign-off. For day-to-day team metrics.
Tier 2
Role-gated: only designated users can define. Multi-approver review required. Template-generated SQL gets a lighter review path. For board-level reporting.
Experimental metrics ship fast with self-serve release. Operational metrics need owner approval. Financial metrics require multi-approver review. The rigor matches the stakes.
The "Single Version of the Truth" is a myth that creates bottlenecks. ClariLayer supports a shared core with intentional, transparent deltas — governed, versioned, and auditable.
Once a metric version is released, it is never changed. Iteration means creating a new version. Full version history with human-readable diffs for every metric.
The full AI conversation behind every definition is preserved. "Why did we exclude refunds from MRR?" — the actual reasoning chain, not just a changelog entry.
Every approved metric generates a pre-validated GitHub PR with contract YAML, SQL artifacts, and a validation report. Engineering reviews and merges in minutes.
The conversation audit trail is institutional knowledge that cannot be recreated. After 12 months with 50+ governed metrics, migrating means losing the reasoning behind every definition.
“Why did we exclude refunds from MRR?” — the actual reasoning chain, not a changelog entry.
“Who approved this churn definition?” — the full approval chain with timestamps.
“When was this last validated?” — validation evidence attached to every version.
Join the companies building a trusted context layer for their AI agents and business teams.
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