The institutional memory
for your infrastructure.
Monitoring · ITSM · AI diagnostics · compliance — one platform
Cortex captures every incident, every resolution, every pattern — and pays it forward. Your team never fights the same fire twice.
- Knowledge outlives tenure. Your senior engineer's fixes stay after they resign.
- High-confidence remediations run themselves. You set the gate; every action is reversible.
- Every CIO figure cites a source record — not an inference.
This site runs on Cortex. So does a live credit-union demo at cascadia.corengram.ai.
- First topology in 60 seconds
- On-prem, hybrid, or SaaS
- BYOK AI (Anthropic / OpenAI / Gemini)
- GLBA / SOC 2 / HIPAA / PCI-DSS ready
You're buying four tools and still paying this tax
Monitoring, ITSM, AIOps, and a CMDB — four stacks, four renewals, and the same three problems.
Alert fatigue is burning on-call
One upstream failure fires 1,000 alerts. Your on-call wastes an hour finding the root cause topology would answer in seconds. Your SRE team is leaving for a company that doesn't page them seven times a night.
Knowledge walks out the door
Your principal engineer gives notice and takes ten years of "the weird firmware thing on blade 7 during B-side failover" with them. Nobody wrote it down. Runbooks wouldn't have captured it anyway. The next P1 costs two hours and three war-room invites you didn't need to send.
Same incident, different quarter
It happened last March. Nobody remembers the fix. The runbook is six versions stale. The war room starts from scratch, on a Saturday, with the same three people asking "did anyone change anything?" The answer is yes — and your monitor doesn't know.
How Cortex works
Six steps from noise to institutional memory
Collect
33 collectors pull from your existing stack. Prometheus, Datadog, CloudWatch, vSphere, NetApp, SNMP — no rip and replace.
Detect
Real-time anomaly detection with online baselines — learns from day one. No training window, no cloud lock-in, no LLM token spend to score a metric.
Correlate
Topology-aware grouping reduces 1,000 alerts to 1 incident. Dependency analysis finds the upstream cause, not the downstream symptoms.
Remember
Every resolution is captured and linked to symptoms, root cause, affected systems, and the fix. Searchable forever. Context is never lost.
Heal
Playbook-based remediation fires automatically when confidence is high enough. Below the threshold, it suggests the fix and waits for approval.
Learn
Every success and failure adjusts pattern confidence. The system gets better. Operator feedback is first-class — approve, reject, annotate, suppress.
What makes Cortex different
Not another dashboard for dashboards. A system that remembers, reasons, and cites its work.
Institutional Memory
Every resolution becomes a structured, searchable artifact — symptoms, root cause, affected systems, the fix, who wrote it, when. Similar symptoms surface historical resolutions via Jaccard similarity on symptom tokens plus semantic embedding — not keyword search, not an LLM guessing. Your team's experience outlives any one engineer's tenure.
Living Topology
A dependency map built from how your infrastructure actually fails — alert co-occurrence, metric correlation, real packet flows — not from a hand-curated CMDB that went stale six months ago. Cypher queries via Apache AGE traverse "disk full on storage-array-7" to "$15K/hr revenue exposure" in milliseconds, and they cite every edge.
Self-Healing
YAML playbook remediation with confidence scoring on every pattern. Above your threshold, it fires automatically and records the outcome. Below, it suggests the fix and waits for approval — with the full evidence chain displayed. Failures adjust confidence down, successes up. You set the gate. You can roll back any action.
Honest AI — Every Figure Cites Its Source
Every precedent citation is scored 0–100 at resolve time. Every prevented-outage claim has a per-record appendix with the threshold rule that selected it. Every AI diagnosis names the tools it called and the records it consulted. No black-box AIOps score, no "trust us, it's magic." Below is verbatim Atlas output from a real Cascadia P1 — confidence 0.78, 11 tool calls, two cited prior records:
Hypothesized chain: Evening peak member traffic surge → login
endpoint resource exhaustion (connection pool saturation, worker
thread limits, or upstream auth/session dependency failure) →
HTTP 503 responses. Confirmed in 1 prior incident at this
organization (inc-p1-online-banking-evening-000, 2026-01-31,
resolved in ~60 min). This is the first confirmed recurrence.
Patterns considered but rejected:
• resolution-incident-cortex-pg-1777163105 — matched
on symptoms (service degradation) but applies to cortex-pg
with stale-table-statistics root cause — different CI class.
• resolution-incident-cortex-app-1777141464 — matched
on worker exhaustion pattern, but applies to cortex-app's
Gunicorn/SSE stack — no evidence svc-online-banking uses it.
• pattern-cascadia-threshold-blip — rejected
because the alert hasn't self-resolved within 5 min and
member complaints are rising — sustained outage, not blip.Note what Atlas doesn't do: pick the first plausible match. It considered three other resolutions and explicitly explained why each one was rejected. That — not the recommendation itself — is what makes the diagnosis defensible to the CIO who'll be asked, "did your AI guess?"
Progressive Trust
Start read-only. Cortex watches, learns, and recommends. Add approval gates when your team's comfortable. Move to full automation per-system, not all-or-nothing. Every action writes a tamper-evident audit entry tying it to a user, a reason, and a reversible diff. Roll back in one click. Never stuck with automation you don't trust yet.
Service Desk That Thinks
Full ITSM — incidents, problems, changes, catalog, CMDB — with a CSDM-aligned data model that imports from ServiceNow in one command. New tickets arrive pre-enriched: topology context, correlated changes, known errors, suggested runbooks with citation-quality scoring. On-call doesn't escalate for context because the context is already on the ticket. Customer extensions are data, not code — they survive every upgrade.
Pre-Investigation Briefing — The Agent Looks First
Before our diagnostic agent touches an alert, it reads a deterministic briefing: every release executing in the blast radius, every change touching the affected stack in the last two hours, every active engineering session, every neighbor incident on the topology, every active maintenance window. The agent doesn't have to remember to check — the briefing always runs first, and every finding cites its source record. Cross-domain causality (a database slowdown caused by the release that touched an upstream app tier twenty minutes ago) becomes obvious, not a second-pass discovery.
=== INVESTIGATION BRIEFING ===
System: svc-online-banking | Alert: high-latency | Window: 2h
ACTIVE RELEASES IN BLAST RADIUS (1):
- REL-00004: 2026-Q2 core-banking batch — currently executing
(bundles 3 changes) [LIKELY CAUSE]
RECENT CHANGES TOUCHING THIS STACK (2):
- CHG-00123: Patch svc-branch-print-01 (implementing,
risk=moderate) [LIKELY CAUSE]
- CHG-00124: Rotate session-cache Redis creds (scheduled, risk=low)
ACTIVE ENGINEERING WORK (1):
- alice: Refactor payment pipeline (in-progress)
ACTIVE MAINTENANCE / BLACKOUT WINDOWS (1):
- Month-End Close (4 systems) — ends 2026-04-30 [LIKELY CAUSE]
CORRELATED INCIDENTS ON NEIGHBORS (1):
- INC-001: DB timeout on svc-core-db (open) [LIKELY CAUSE]Every finding above is a real KG record — a release ID, a change ID, a session slug, a blackout window, an incident on a topology neighbor. The diagnosis below cites them by name.
One platform. Six products. Replaces your stack.
Every module feeds the same knowledge graph. Each makes the others smarter. Missing modules degrade gracefully — deploy only what you need. One renewal, one login, one source of truth.
Cortex
Infrastructure Intelligence · replaces Datadog / New Relic AIOps
Self-healing monitoring with 33+ collectors, online-baseline anomaly detection, living topology, alert correlation, institutional memory, causal-pattern learning, and predictive capacity forecasting. The foundation everything else plugs into.
- 1,000 alerts → 1 root-cause incident
- Blast radius in milliseconds
- Patterns compound in confidence as they fire
Service Desk
Enterprise ITSM · replaces ServiceNow / BMC Remedy
Full ITSM with a CSDM-aligned CMDB: incidents, problems, changes, catalog, and a knowledge base that auto-populates from resolved tickets. Tickets arrive pre-enriched with topology, suggested runbooks, and blast radius. One-command migration from ServiceNow. Customer extensions stored as data, not code.
- Incidents, Problems, Changes, Catalog, CMDB
- Pre-enriched tickets save on-call escalations
- Customer fields survive every upgrade
Atlas AI
Agentic Diagnostics · replaces BigPanda / Moogsoft AIOps
Autonomous agent with tool-use: searches operational history, walks topology, correlates recent changes, consults institutional memory, runs simulation scenarios, and returns a structured diagnosis with confidence and citations. BYOK — Anthropic, OpenAI, or Gemini. On-prem air-gap friendly. Graceful degradation to deterministic scoring when no key is configured.
- Structured RCA with cited evidence
- Searches history before the LLM guesses
- Bring your own API key — no lock-in
FinOps
Cloud Cost Management · replaces Apptio Cloudability / CloudHealth
Azure, AWS, and GCP unified cost visibility with budget alerts, waste detection, and per-team chargeback. The difference: cost feeds back into change simulation and topology — you see the price tag and the blast radius on the same pre-deploy report.
- Cost by resource, service, and team
- Waste finder with reclaim estimates
- Pre-deploy cost + risk on one screen
Compliance
Automated Evidence · replaces Drata / Vanta
SOC 2, GLBA, HIPAA, PCI-DSS, ISO 27001 evidence generated from actual operational records — not vendor questionnaires. Push-button audit reports cite source KG entries. Drift detection opens remediation tickets when a control degrades. Your examiner gets a regenerable artifact, not a screenshot from last week.
- 5 frameworks, evidence from source records
- Drift detection auto-opens remediation tickets
- Regenerable on demand — no cached inference
Deploy
Infrastructure Orchestration · complements Terraform Cloud / Spacelift
Terraform orchestration with landing zones (Azure CAF, AWS Well-Architected, GCP), environment promotion gates, and drift detection. Every plan runs through blast-radius simulation and policy-as-code compliance checks before touching production. Simulation results attach to the PR; approval workflow is scoped per environment.
- Blast radius + cost + risk on every plan
- Per-env promotion gates (tests / cost / drift / manual)
- Drift detection auto-opens remediation changes
See the receipts.
These figures are pulled live from cascadia.corengram.ai — a real Cortex tenant modeling a regional credit union with 140+ incidents, 30 work sessions, and 90 days of operational history. Every number below traces to a source record. Open the dashboard, poke around, regenerate the PDF yourself.
Live as of — · — incidents in window
The honest part. The prevented-outage count comes with a per-record appendix naming
every session that contributed — the threshold rule that selected it, the risk score, and a one-sentence AI-written
business-risk narrative. The citation rate's 18% isn't a self-reported average: each tag was written at ticket-resolve time
by a named resolver via the /resolve
API and carries an audit event. Avg quality is the weighted mean across strong / moderate / weak matches, scored at
citation time. No cached inference, no vanity metrics.
API key available on request — auth keeps the demo clean between visitors. Ask and we'll send you one.
Break something. Watch Cortex fix it.
The Cascadia demo runs a real, writable Cortex tenant. Trigger a failure through the Simulate page and watch it propagate through the topology, fire the matched runbook, and post the resolution to institutional memory — live. Three minutes end-to-end. No slides.
Two demo environments: cascadia.corengram.ai (credit-union workload, 140+ incidents seeded) and cortex.corengram.ai (monitoring CorEngram AI's own infrastructure — every incident is real). API key available on request.
How it learns
Cortex gets smarter the longer it runs. Here's the ramp.
Discovers your infrastructure
Port scanning, Docker API, Kubernetes API, cloud provider metadata. Automatic collector assignment. First topology edges appear.
Maps topology, identifies single points of failure
Dependency map built from alert co-occurrence and metric correlation. Single points of failure flagged. Blast radius estimates on every system.
Baselines established, anomalies detected
Welford's online algorithm learns normal. No training window — baselines start from the first data point and refine continuously.
Institutional memory growing, patterns forming
Resolutions linked to symptoms and root causes. Causal patterns learned from incident sequences. Runbooks auto-generated from history.
Self-healing with confidence, executive insights dense with data
High-confidence patterns execute automatically. Capacity forecasts predict issues weeks out. CIO dashboards show trends, not just status.
Built for regulated industries
Examiner-ready evidence generated from live operational records. Every control maps to a KG entry with a timestamp, an actor, and a diff — not a vendor questionnaire from 2023.
Credit Unions & Banks
7/7 Safeguards Rule controls mapped to KG entries. 7-year audit retention. Access controls, encryption-at-rest, incident response, vendor oversight — all cite source records. NCUA § 748.2 change-control evidence exports in a single report.
Type II Ready
Trust Service Criteria covered across Security, Availability, Processing Integrity, Confidentiality, and Privacy. Continuous evidence — not a once-a-year scramble. Change control, access reviews, incident response tied to actual tickets.
DSS 4.0
Payment data isolation tracked in the CMDB. Role-based access enforced and audited. Change tracking with blast-radius impact on CDE boundaries. Quarterly ASV scan evidence integrates via the Compliance collector.
ePHI Handling
Administrative, physical, and technical safeguards. PHI access audit trail with tamper-evident logging. Risk assessment artifacts regenerable on demand. BAA-compatible deployment architecture — on-prem or private Azure.
Cortex is compliance-ready infrastructure — you still bring the audit relationship and the formal attestation. What Cortex eliminates is the evidence-gathering scramble and the gap between what your controls say and what your operations actually did. Ask to see a live regulator-ready export from the Cascadia demo.
We run Cortex on Cortex.
Our production instance at cortex.corengram.ai monitors CorEngram AI's own infrastructure — every container, every Postgres pool, every Azure resource behind this website. Every incident, every learned pattern, every compliance record shown there is real. We eat our own dog food daily, which is how we find the bugs before you do.
Plugs into your existing stack
33 collectors across every major infrastructure category. Cortex reads your tools, doesn't replace them — until you're ready. Then it does, one module at a time.
Plus an AI-powered connector generator: paste an API doc URL, get a validated collector in under 10 minutes.
Built-in safety sandbox blocks subprocess, eval, pickle, and unsafe network patterns before any new collector touches production.
See it on your infrastructure
30 minutes. A shared screen. We run Cortex against a slice of your actual environment — your monitoring feeds, your recent incidents, your topology. You see the first auto-discovered dependency map, the first institutional-memory match on a real historical incident, and the first compliance-evidence export. No slides. If it isn't useful in 30 minutes, we're wasting each other's time.
hello@corengram.ai