See failures before they become incidents.
Opsalytic brings machine-learning anomaly detection, automated root-cause analysis, and self-healing automation to your infrastructure — trained on your fleet, deployed inside your network.
// tuned to you
Models learn each host's normal rhythm — no generic thresholds, no alert storms.
// stack-native
Works with the Prometheus, ELK, Grafana & Ansible you already run. No rip-and-replace.
// production-proven
The same pipeline built and operated on a live enterprise server fleet — not slideware.
From noisy dashboards to answers.
Four capabilities that close the loop from signal to resolution — deployed as a system, not a pile of tools.
Predictive anomaly detection
ML models (LSTM & friends) learn the baseline behaviour of every host — logs, load, run-queue, memory — and flag drift in real time, before it turns into an outage.
DETECTAutomated root-cause analysis
The moment a signal deviates, RCA collectors gather the right diagnostics and correlate them into a probable cause — so your team gets an answer, not a wall of red.
DIAGNOSESelf-healing automation
Ansible-driven remediation playbooks act on detected conditions — restart, drain, scale, reroute — closing the loop from detection to fix on the failure modes you approve.
HEALPrivate, on-prem AI
Models and LLMs that run on your hardware, inside your perimeter. Root-cause summaries and ops copilots without a single byte of telemetry leaving your network.
SOVEREIGNA pipeline, in four stages.
Each engagement follows the same path — you can enter at any stage and stop wherever the value is.
Instrument
Establish clean, labelled telemetry from your fleet — logs, metrics, load signals — and close the gaps that make detection unreliable.
Detect
Train per-host models on your own baseline and surface true anomalies in real time, with the noise-suppression that keeps teams trusting the alerts.
Diagnose
Automate diagnostic collection and correlation so every anomaly arrives with a probable root cause attached, not a triage backlog.
Automate
Wire safe, reversible remediation for the failure modes you sign off on — turning repeat incidents into non-events.
Three ways to start.
Fixed-scope where it should be, flexible where it matters. Every engagement is priced to your fleet after a short scoping call.
Readiness Sprint
A clear-eyed audit of where you are and the fastest path to value — with a working proof, not just a slide deck.
- AIOps & observability maturity audit
- Telemetry & data-gap analysis
- Proof-of-value model on one service group
- Prioritised roadmap & business case
Implementation
Anomaly detection and RCA in production across your fleet, with your team trained to own it.
- Production anomaly models, fleet-wide
- RCA automation & correlation pipeline
- Dashboards, alerting & runbooks
- Full handover & team enablement
Managed AIOps
We run and evolve the system with you — expanding coverage and turning incidents into automation.
- Model tuning & drift management
- Coverage expansion to new services
- New self-healing playbooks each cycle
- Monthly reliability reporting
Built in production, not on slides.
Opsalytic is led by a systems engineer who designed and operates ML-driven monitoring for a live enterprise server fleet — the same anomaly models, RCA collectors, and self-healing playbooks we bring to your infrastructure.
That means no black boxes and no rip-and-replace. We work with the stack you already run, we show our working, and we hand it over so your team can own it.
“Most monitoring tells you something broke. The point of AIOps is to know it's about to — and to have already started fixing it.”
The identity, in brief.
The mark is a telemetry trace catching a single anomaly — the whole business in one glyph.
Let's find the incident you haven't had yet.
A 30-minute discovery call: we look at your current monitoring, spot where anomaly detection would pay off first, and tell you honestly whether it's worth it.
Book a discovery call