Neuri
Adaptive Root Cause Analysis Engine, helps reduce time, efforts and budget spent on Investigations
The problem
Root cause means slow dashboard splunking and sequential troubleshooting, while the incident keeps burning.
How Neuri solves it
- Finds root causes within seconds of an incident firing reading logs, traces, metrics, change logs and code directly.
- Confidence Thresholds as Analytics Quality Gate
- Every reasoning it builds feeds an incremental inductive memory library.
- Steering lets you edit and redirect the reasoning steps and re-execute against the same incident.
- Human-in-the-loop approval gates what enters the library.
payments-api OOMKill cascade — 2026-07-04
payments-api · payments-worker
91%
Root cause found
Deploy a3f9c2 cut the payments-api memory limit from 512Mi to 256Mi — the container OOMKills under normal load.
Evidence
Reasoning steps
Deploy a3f9c2 lowered the payments-api memory limit from 512Mi to 256Mi
Kubernetes OOMKills the container repeatedly, producing a restart cascade across all 3 replicas
Review history
APPROVED by @priya · 14:31
What changes once Neuri is in the loop.
Before Neuri
4 hr
Time lost per incident
$20k
Budget burned monthly
100%
Senior Team Member Capacity Engaged
10+
Tools and Interfaces Multitasked
30 min
Documentation Toil
After Neuri
90%
Faster Investigation (MTTI)
70%
Faster root cause (MTTR)
15+
Tools at one place
$200k
Saved annually
95%
Tribal Knowledge Capture
Inside Neuri's reasoning
Signal ingestion
The moment an alert fires, Neuri reads logs, traces, metrics, change logs and code directly — no engineer has to open a single dashboard first.
Hypothesis formation
Anomalies across every signal are cross-correlated into a ranked set of root-cause hypotheses, instead of one dashboard being checked at a time.
Evidence-scored reasoning
The strongest hypothesis becomes a structured RCA with a numeric confidence score, citing the exact log lines, traces and commits behind it.
Steering & re-execution
If the reasoning missed something, an engineer edits or redirects the logical steps and re-runs Neuri against the same incident for a sharper result.
Human approval & memory
Nothing enters the inductive memory library without manual approval — every accepted RCA makes the next investigation faster and more accurate.
Features and Capabilities
Adaptive learning curve
An incremental inductive memory library that keeps building each time a new reasoning is formed from logs, traces, metrics, change logs and code.
Multi-source correlation
Correlates logs, traces, metrics, change logs and code in a single pass instead of checking one signal at a time.
Steering capability
Edit and redirect the logical reasoning steps, then execute against the same incident again to extract a more accurate RCA by manual intervention.
Confidence-scored output
Every RCA ships with a numeric confidence score and the exact evidence trail behind it, not just a guess.
Human in the loop
Every RCA reasoning undergoes Quality check with manual approval before it is added to the library.
Redaction
PII and secure information masking, including email, name, IP and phone number, to avoid any data leakage to the LLM.
Guardrails
Control over investigation bounds with hard limits on reasoning loops, token usage, LLM response bounds and much more.
Evaluation benchmarks
Accuracy gates with confidence scores — 80% reasoning accuracy when all reasoning prerequisites are provided.
How accurate is Neuri
80%
Accurate
Integrated with the production tools.
Human in the loop
Every RCA and runbook reasoning undergoes Quality check with manual approval before it enters the library.
Steering capability
Edit and redirect the reasoning and tool-usage steps, then re-execute to sharpen the result.
Guardrails
Hard limits on reasoning loops, tool-use depth and iterations, token usage and LLM response bounds.
Redaction
PII and Sensitive information masking. Strict data governance preventing data leakage to LLM.
Evaluation benchmarks
Accuracy gates with confidence scores and validation benchmarks.
Shadow mode
Simulate against the live system with no write provision. Runbooks and playbooks move to live only once approved.
Connects to your entire stack
Prometheus
Metrics
Datadog
Metrics
CloudWatch
Metrics
New Relic
Metrics
Dynatrace
Metrics
Loki
Logs
Elastic / ELK
Logs
Datadog Logs
Logs
CloudWatch Logs
Logs
Jaeger
Traces
Tempo
Traces
Datadog APM
Traces
Sentry
Traces
Kubernetes
Infrastructure
AWS
Infrastructure
GCP
Infrastructure
Azure
Infrastructure
GitHub
Code & Deploys
GitLab
Code & Deploys
ArgoCD
Code & Deploys
FluidifyAI Regen
Incidents
PagerDuty
Incidents
OpsGenie
Incidents
Built to be trusted with production
Bring Your Own Key (BYOK)
Bring your own LLM key, with multi-vendor multi-model support.
Data Leakage Prevention
PII and Sensitive information masking with strict data governance layers.
Multiple Deployment Options
On-prem, Air-gapped and Private Cloud, Managed Cloud SaaS Deployments, configured and validated by a dedicated Forward Deployment Engineer.
Access Control and Auditing
RBAC, MFA, Custom SSO/SCIM provisioning and Audit trails
Compliant on
Deploys to
Where does it sit in the Suite?
Neuri owns root cause analysis in the AI SRE Suite — replicate the issue, troubleshoot and detect the root cause. It takes the structured incident record Regen creates, and hands a confidence-scored diagnosis to Reflex to act on, or to Gills so anyone can ask about it in plain conversation.
Root cause analysis
Neuri is available both as open-source and as a managed cloud service.
For open-source deployment, run it on your Kubernetes cluster, a Docker Compose stack, or spin it up locally in seconds. Your data stays on your infrastructure.
- Docker Compose quick start up in under 5 minutes
- Helm chart for Kubernetes with TLS + ingress
- Published image on ghcr.io/fluidifyai/neuri
- No vendor lock-in your infra, your data
Don't want to self-host?
We can manage Neuri for you - fully hosted, maintained, and updated. See managed plans →
git clone https://github.com/FluidifyAI/Neuri cd Neuri cp .env.example .env # Edit .env with your values, then: docker compose up -d # Open https://github.com/FluidifyAI/Neuri
Frequently asked questions
Yes. Neuri is available in open source at github.com/FluidifyAI for self-hosting and testing, and is included on the Free tier alongside Regen. Pro adds the complete integration stack and extended reasoning with steering mode.
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