The Platform

One causal entity graph. Four AI engines. Built for enterprise engineering teams who need answers, not dashboards.

⬡ Platform overview → ◯ Four engines → ▶ How it works → → Start free trial →

What we solve

Applicare enables teams to observe, automate, and resolve incidents faster across every stack.

★ Customer stories → → Try it free → ◯ Platform overview →
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Featured Case Studies
AeroMexico
Digital ticketing · MTTR 4.5h → 11min
Leading Private Bank
MTTR 3.2h → 18min · first month
Mediclinic
Audit prep 11 weeks → 18 days
NTT DATA
80% on-call page reduction
Danube Group
94% SLO compliance
ONP
0 violations at last audit
Seygen
78% downtime reduction · GxP compliance
Insurance Tech Platform
67% P1 reduction · $2.4M saved
IIS & Server Availability
100% SLA report accuracy
Health Check Offering
4.2x ROI · 48hr delivery
Bank of Muscat
99.95% core banking uptime
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Solutions · Google Cloud Platform

Understand every Google Cloud incident in under 60 seconds.

From GKE to Cloud SQL to Pub/Sub, Applicare automatically maps dependencies, identifies root causes, explains customer impact, and recommends remediation before incidents become outages.

Applicare — GCP Incident Intelligence⬤ Live
GCP Architecture Flow
⚙ GKE
📨 Pub/Sub
⚡ Functions
🗄 Cloud SQL
🛒 Checkout
Latency
2,847ms
checkout · p99 ↑ 18×
Cloud SQL Conn
94%
pool near exhaustion
✓ Root Cause Identified — Deploy #4821 introduced N+1 query pattern. Cloud SQL connection pool exhausted (94%). Pub/Sub backlog growing. → Recommended Remediation: Roll back deploy #4821 or apply query cache patch.
<60s
Root cause identification across all GCP services
38%
Average GCP cost reduction after deployment
25+
Google Cloud services monitored natively
99.99%
Application availability for Applicare customers
The Observability Gap

Why native monitoring isn't enough.

Google Cloud Operations surfaces signals. Applicare delivers causality — the difference between knowing something is wrong and knowing exactly what to do about it.

Google Cloud Operations tells you
  • CPU is high
  • Errors increased
  • Latency is rising
You still have to find out why — hours of manual correlation across dashboards, logs, and teams.
Applicare tells you
  • What changed (deploy, config, traffic shift)
  • Why it happened (root cause service & query)
  • Which services are affected and in what order
  • What should happen next (remediation steps)
Causality, context, and action — in under 60 seconds.
SIGNALS
Metrics · Logs · Traces
CONTEXT
Deploys · Changes
CAUSALITY
Root Cause · Impact
ACTION
Remediation Steps
Incident Investigation

See how Applicare investigates incidents.

10:03 AM
Deployment #4821 released
New checkout service version deployed to GKE prod cluster
10:05 AM
Cloud SQL connections spike
Connection pool utilisation rises from 42% → 94%
10:06 AM
Pub/Sub backlog increases
order-events topic: 12,000 unprocessed messages and growing
10:07 AM
Checkout latency rises
p99 latency: 156ms → 2,847ms · error rate +4.2%
10:08 AM
🧠 ArcIn identifies root cause
N+1 query in deploy #4821 · SQL pool exhausted · 3-service cascade confirmed
10:09 AM
⚡ IntelliTune recommends remediation
Option A: rollback deploy. Option B: apply query cache patch (no downtime)
ArcIn — Causality Analysis⬤ Resolved 10:09
🧠 ArcIn Root Cause:
Deploy #4821 introduced 23 additional SQL queries per checkout transaction (N+1 on cart.getItems()). Under load, Cloud SQL connection pool (limit: 200) reached 188/200. Pub/Sub consumers blocked waiting for SQL. Full cascade took 4 minutes.
⚡ IntelliTune:
Recommended: eager-load cart items with SELECT IN (1 query vs 23). Auto-patch available. Estimated resolution: 4 minutes, zero downtime.
Traditional Monitoring
6–20
minutes to understand
Applicare
<60s
to root cause + remediation
Entity Graph

Every dependency. One graph.

Every deployment, service, database, queue, API, and customer transaction represented in a continuously updated causal relationship graph — auto-discovered in under 12 seconds.

Live Entity Graph — Google Cloud
GKE Cluster (prod-us-central1)Healthy
└─ depends on ─────────────────
Pub/Sub (order-events)Backlog ↑
└─ triggers ─────────────────
Cloud Functions (order-processor)Running
└─ queries ──────────────────
Cloud SQL (orders-db)🔴 Root Cause
└─ impacts ──────────────────
Customer Checkout FlowLatency 2.8s
└─ analysed by ──────────────
ArcIn Causality Engine✓ Root Cause + Fix
Auto-discovered in 11.4s · Updated every 15s · 247 entities mapped
🔗
Cross-service causal topology
Every GCP service, deploy, config change, and user transaction linked in a living graph. Incidents spanning 5 services surface as one root cause, not five alerts.
Auto-discovered · no manual mapping required
Deploy-correlated intelligence
Every deployment tracked against performance baselines. Regressions detected within seconds — before the on-call pager fires.
Deployment gates · automatic rollback triggers
💡
Customer impact quantification
Each incident correlated with affected user sessions, transactions, and revenue impact — so you prioritise what matters.
Business context on every alert
Native Integrations

Built for modern Google Cloud environments.

Deep native integrations with 25+ Google Cloud services — no custom exporters, no agents to manage.

GKE
🗄
Cloud SQL
🚀
Cloud Run
📨
Pub/Sub
📊
BigQuery
🗂
Cloud Storage
Cloud Functions
🔒
IAM
🌐
VPC
☸️
Anthos
🔷
Spanner
📡
Cloud CDN
Load Balancing
🛡
Cloud Armor
📋
Cloud Logging
Customer Outcomes

Proven results across industries.

Global Retail Enterprise
Challenge: Checkout failures during peak sales events causing revenue loss and customer complaints.
faster incident resolution
99.99%
uptime achieved
65%
fewer customer complaints
Financial Services Platform
Challenge: Cross-region latency issues creating Sev-1 incidents and unpredictable infrastructure spend.
82%
reduction in MTTR
41%
lower infra spend
96%
fewer Sev-1 incidents
Quick Start

Start understanding your cloud in minutes.

01
Connect your GCP projects
OAuth2 or service account — one click to link all your GCP projects and regions. No agents to deploy.
02
Applicare maps dependencies
Entity graph auto-discovery runs immediately — GKE, Cloud SQL, Pub/Sub, and Functions all connected in under 12 seconds.
03
Investigate incidents immediately
ArcIn begins correlating signals. First root cause identification available within your first deployment cycle.
Average time to first insight: under 30 minutes
Ready to see causality?

Google Cloud Monitoring shows you signals.
Applicare shows you causality.

Understand what changed, why it happened, how it impacts customers, and what to do next — in under 60 seconds.