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The four-layer Reliability Intelligence loop.

Most reliability tools are point solutions: one layer of intelligence, then a long manual workflow on top. Causum integrates four layers into a single compounding loop. Each layer makes the next one smarter.

The core insight

Any one layer is a feature. The loop is the product.

  • Other tools correlate alerts

    But don't read your code, so they're configured by humans and stay stale.

  • Other tools detect anomalies

    But don't know which anomalies matter to your business.

  • Other tools execute runbooks

    But don't gate them behind confidence thresholds or domain context.

  • Other tools learn from operators

    But require months of manual setup before learning can start.

Causum closes these gaps because every layer feeds the next:

Domain Intelligence produces specs → Signal Intelligence runs them → RCA uses them as rules → Remediation's audit trail feeds RCA learning → operator feedback recalibrates Signal Intelligence.

Layer 1

🧬Domain Intelligence

Reads your code. Infers what should be monitored.

The Codebase Explorer Agent reads your application repository, schema, and production data sample. From these, it generates the artifacts that should have been your monitoring baseline from day one.

  • 🔀

    Business entity state machines

    Order flows, checkout flows, payment lifecycles — with P50/P95/P99 transition latencies.

  • 🧮

    Data invariants

    Business rules implied by your schema, including violations that exist right now.

  • ⚠️

    Anti-patterns with business impact

    Not generic linter findings. Domain-specific reliability risks with quantified impact.

  • 📡

    Auto-generated sensors

    For everything above. Ready for Signal Intelligence to operate.

Layer 2

📡Signal Intelligence

Auto-calibrating, entity-aware anomaly detection.

Static thresholds break. Within a quarter they're either firing on every minor blip or missing the meaningful ones. Signal Intelligence is the layer that runs the sensors Domain Intelligence generated — without human tuning.

  • 📊

    Auto-calibrating

    Per entity, per mode (holiday, promo, post-release). No human tuning required.

  • 🌊

    Seasonal aware

    Knows about your demand cycles and adjusts envelopes accordingly.

  • 🧬

    Entity-level

    "Order stuck in CHECKOUT_INITIATED > 8 min" — not "p99 latency: 340ms."

  • 🪞

    Shadow mode first

    Runs in observe mode against your production stream until your team approves promotion.

Layer 3

🧠RCA Intelligence

Root cause in minutes, with evidence.

Other tools correlate alerts. RCA Intelligence reasons over a causal graph built from the entity state machines, signal timeline, deploy history, and infrastructure dependencies — then shows its work.

  • 🎯

    Composite scoring

    Every candidate root cause has a confidence score derived from multiple signal types.

  • 🔗

    Causal chain reasoning

    Not just "these alerts correlate" — "this caused that, which caused that."

  • 📚

    Learned reranker

    Improves with every postmortem your team confirms.

  • 🔍

    Always shows its work

    Every recommendation links back to the raw metrics, traces, and log lines.

Layer 4

⚙️Remediation Intelligence

Graduated autonomy. Six guardrails. Kill switch.

This is the layer most SREs are skeptical of, and rightly so. Causum's remediation engine is designed around the assumption that trust is earned, not granted. New services and new actions start at Observe. Promotion is explicit. Auto-demotion on failure.

  • 🎚

    Observe by default

    New services start at Observe. Promotion is explicit. Auto-demotion on failure.

  • 🛡

    Six guardrails on every action

    Allowlist · confidence · blast radius · approval gate · pre/post checks · kill switch.

  • 📜

    Cryptographic audit trail

    Every action immutably chained. SIEM-streamable. Forever-queryable.

  • Kill switch always visible

    Tenant-wide halt one click away. Always rendered, regardless of autonomy level.

Integration surface

Works with your existing stack.

Port-agnostic. We don't replace your observability tools — we read from them via their native APIs.

PortOOTB adapters
MetricsGrafana, Datadog, Prometheus, AppDynamics
TracesAppDynamics, Datadog APM, Jaeger, OpenTelemetry
LogsOpenSearch, Splunk, Elasticsearch, Loki
IncidentsServiceNow, Jira Service Management
AlertingPagerDuty, OpsGenie, VictorOps
SCMGitHub, GitLab, Bitbucket
DatabasePostgreSQL, MySQL, Oracle
Identity (SSO)Okta, Azure AD, generic SAML/OIDC

No data re-ingestion. No agent installs. No new dashboards your team has to learn.

See the loop in action.

The shortest path to understanding Causum is to see Domain Intelligence run against a real codebase. Talk to our forward-deployed engineering team about a 30-minute walk-through.