Monitoring tells you something broke. AIOps tells you what, why and what to do.
Modern estates produce more signals than people can read: thousands of alerts a day from servers, cloud services, networks, databases and applications, most of them echoes of the same few problems. Gartner describes AIOps as combining big data and machine learning to automate IT operations processes such as event correlation, anomaly detection and determining causality. XcellAI AIOps brings that to your estate as a service — the platform, the models and the people who act on them.
We ingest your metrics, logs, traces and events — natively or through OpenTelemetry — learn what normal looks like for each service, group related alerts into incidents, rank the likely root cause on your service topology and, where you allow it, run pre-approved fixes. Every incident is worked by the XcellHost 24×7 NOC in Mumbai, ticketed in your ITSM tool and reported monthly in rupees and minutes.
Duplicates removed, related alerts grouped by time, topology and text into one incident.
Dynamic baselines per metric and hour of day — no more guessing static thresholds.
Dependencies mapped, so the failing database is flagged, not the forty symptoms above it.
Disk, CPU, memory and licence trends forecast weeks ahead, before they become outages.
Runbooks that restart, clear, scale or roll back — behind a human approval gate you control.
Metrics, logs and traces in one view, with OpenTelemetry so you are not locked to one vendor.
Plain-English incident summaries, timelines and draft post-incident reviews for engineers to check.
Incidents open, update and close in leading ITSM tools* with full context attached.
Six stages from raw signal to a fixed problem.
Click a stage to see what happens there and who is involved.
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Where AIOps pays back first.
Six situations we see across Indian estates. Each shows the signal, what AIOps does with it, and the outcome you can measure.
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Models find the problem. Our NOC owns it.
AIOps without people is just another dashboard. Every plan is worked by the same 24×7 NOC that runs our managed operations services.
L1–L3 engineers on shift around the clock; P1 incidents worked live, not queued.
01Correlation rules, baselines and suppression windows reviewed every month.
02You choose which runbooks run automatically and which wait for a named approver.
03Tickets and evidence live in your tool; we work inside your process.
04Noise, MTTR, auto-resolved incidents and capacity forecasts, with next month's fixes.
05Platform, service and add-ons on one GST invoice from an Indian company.
06Faster detection and complete logs help you meet Indian rules.
AIOps does not make you compliant on its own. It shortens the time to know, keeps the evidence and gives your incident team a timeline they can file.
CERT-In's April 2022 directions require reportable cyber incidents to be reported within 6 hours of noticing them. Correlated incidents with timelines help your team notice sooner and report with facts.
The same directions ask for ICT system logs to be kept for a rolling 180 days within India. We can route and retain the logs AIOps ingests in Indian data centres.
As the DPDP Rules phase in, a personal-data breach must be intimated to the Data Protection Board without delay, with a detailed report within 72 hours. Faster detection and a clean timeline help you meet that.
RBI's IT governance master direction and SEBI's Cybersecurity and Cyber Resilience Framework (CSCRF) expect monitoring, incident management and capacity planning. AIOps reports give you evidence for each.
Regulatory summaries checked October 2026 for orientation only — not legal advice. Your organisation remains responsible for its own reporting and compliance; confirm current requirements with CERT-In, the Data Protection Board, RBI or SEBI.
Priced per estate, per month. Sized by what we watch.
A monitored entity is one host, VM, container cluster, database, network device or service endpoint. Observability platform licences and cloud usage are billed separately at actuals.
See clearly
- Ingest metrics, logs & events
- Event correlation & noise reduction
- Anomaly detection on baselines
- 24×7 NOC triage, P1 worked live
- Tickets in your ITSM or ours
- Monthly noise & MTTR report
Fix faster
- Everything in Essential
- Traces & OpenTelemetry pipeline
- Topology-aware root cause
- Predictive capacity forecasts
- 10 auto-remediation runbooks with approval gates
- GenAI incident summaries
- Quarterly business review
Run at scale
- Everything in Professional
- Named service manager
- Custom models, rules & runbooks
- Log retention in Indian DCs
- BFSI evidence packs (RBI / SEBI)
- Custom SLAs
* Indicative — confirm with XcellHost. INR, excluding 18% GST. Extra monitored entities ₹199* each per month. One-time onboarding and transition ₹24,999*, the same fee as our Cloud Operations and Security Operations onboarding.
Build your AIOps plan. See the rupee total.
Pick a plan, the entities you want watched and any add-ons. Fixed-price items go to the cart; Enterprise comes with a quotation.
Professional · 300 entities
What is the noise costing you?
An illustrative estimate. Every input and both improvement rates are yours to change, and the formula is shown under the result.
alerts/month = alerts/day × 30
triage hours saved = alerts/month × noise reduction × triage min ÷ 60
new MTTR = MTTR × (1 − MTTR improvement)
incident hours saved = incidents × (MTTR − new MTTR) ÷ 60
value = triage hours × engineer ₹/h + incident hours × impact ₹/h
Eight questions. Where does your NOC stand?
Answer for your operations today. You get a maturity level, the gaps that matter most and a suggested starting plan.
Answer the questions
Each answer moves the score. Unanswered questions count as the lowest option.
AIOps, traditional monitoring, or nothing at all.
| What happens | No monitoring | Traditional monitoring | XcellHost AIOps |
|---|---|---|---|
| An outage starts | Users call the helpdesk | Hundreds of threshold alerts fire | One correlated incident opens |
| Slow degradation | Unnoticed until it fails | Missed until a static threshold trips | Flagged when it leaves its baseline |
| Finding the cause | Guesswork across teams | Engineers compare dashboards by hand | Likely root cause ranked on topology |
| Disk or capacity running out | Outage on the day it fills | Alert at 90%, often at night | Forecast weeks ahead, fixed in hours |
| Known, repeat fixes | Whoever is free tries something | Manual steps from a wiki page | Tested runbook after one approval |
| Incident record | None | Written up later from memory | Timeline and summary drafted automatically |
| Logs for CERT-In | Not kept | Scattered across tools, short retention | Centralised, 180-day retention option in India |
| Monthly view | No data | Uptime percentages only | Noise, MTTR, auto-resolved and forecasts |
Live in about six weeks. Measured from day one.
Typical timings for 100–300 monitored entities*. Larger or multi-cloud estates take longer.
- 01DiscoverTools, data sources, services and today's alert volume. Baseline noise and MTTR measured.Week 1*
- 02ConnectMonitoring, logs, cloud and ITSM integrated; OpenTelemetry where needed.Week 1–2*
- 03LearnModels learn baselines; service topology mapped and checked with your team.Week 2–4*
- 04TuneCorrelation rules and suppression tuned on live alerts alongside your engineers.Week 3–5*
- 05Go liveNOC owns the queue; first runbooks enabled behind approval gates.Week 5–6*
- 06ImproveMonthly report, new runbooks, quarterly review of noise and MTTR.ongoing