Your Identity Observability Layer
Connect the identity stack. Correlate across systems. Create a defensible posture baseline that can be rerun and proven over time.
See observity.ai in your environment.
A 30-minute walkthrough against an environment like yours, so you can tell quickly if observity.ai fits.
Four Steps to Defensible Identity Posture
Connect systems. Create the baseline. Finalize accepted findings. Rerun to prove the delta.
Connect
Read-only IAM, HR, ITSM, PAM, and cloud signals
Baseline
Versioned identity posture from live connector data
Finalize
Accepted findings become the trusted record
Rerun
Refresh the baseline and prove the delta
The Layers That Make Identity Observable
Any MCP tool can pull data and write a summary. observity.ai turns that access into durable platform assets: correlation, evidence, validation, memory, and before/after proof.
Connector data in. Defensible posture out.
Connect the IAM stack that matters for the workflow under review. observity.ai analyzes signals across those systems and creates a versioned identity posture baseline in hours, not weeks.
- Live metrics from your enterprise systems via MCP
- Cross-platform gaps surface automatically
- Executive summary, findings, risk scores, and roadmap
- v1.0 identity record delivered in hours — not weeks of manual work
Context that survives the first report.
Baselines can be enriched with benchmarks, compliance context, prior accepted findings, and best practices scoped to your team's industry, frameworks, and goals.
- Benchmark context — automation rates, provisioning SLAs, certification norms
- Framework-aware context — SOX, HIPAA, NIST, ISO 27001 where relevant
- Scoped to your environment's industry and frameworks
- Enterprise organization memory can carry accepted report context forward
Risks invisible to any single tool.
observity.ai correlates identity data across connected systems, surfacing gaps that no single platform can detect on its own.
- Correlates identity records across all connected platforms
- Surfaces cross-platform risks no single tool can see
- Severity-ranked findings auto-classified into the baseline
- Runs automatically — no separate spreadsheet exercise
Know it's right before you present.
AI validation checks the baseline for logical consistency, metric grounding, and narrative coherence. Issues surface as clear flags before you circulate findings broadly.
- Validation warnings appear directly in the baseline
- Issues surface as clear flags before findings are shared broadly
- Generate fix drafts, review the changes, then apply them when ready
Chat with any finding.
Dig Deeper opens a chat scoped to the baseline, finding, or metric you are reviewing. Answers can use report context, connector tool results, and benchmark or compliance research when the question calls for it.
- Scoped chat on any metric or finding
- Answers from report context, connector data, and cited research when available
- Preserve the context needed for stakeholder follow-up
- Conversation persists — pick up where you left off
This finding affects multiple connected systems and exceeds industry benchmarks for acceptable risk thresholds.
One baseline becomes repeatable proof.
Rerun from the accepted baseline with updated connector data. observity.ai detects what changed since the last version, builds the before-and-after comparison into every rerun, and gives teams a repeatable control-verification workflow.
- Rerun the accepted baseline with updated connector data
- Before/after comparison built into every version
- Turn one-time discovery into repeatable proof of improvement
Bring observity.ai into your IAM workflow.
Request a personalized demo to review your current stack, evidence workflow, and what a real rollout would look like.