Early Access · Pilot Program Open

Detect. Predict.
Diagnose. Remediate.

AI-powered observability and autonomous incident response for modern infrastructure.

6
Anomaly Detection Engines
108/sec
Events Processed — Load Tested
1.4–1.7s
Verified Auto-Heal Recovery
40/40
Reliability Tests Passed
Validated on development infrastructure; production deployments are currently in pilot.
Statistical Z-scoreIsolation ForestLSTM Deep DetectorMultivariate CorrelationSeasonal DetectionDrift DetectionCausal Graph RCABlast RadiusDocker Auto-HealRedis WALMulti-Tenant IsolationOpenTelemetryRBAC EnforcementTamper-Evident Audit Statistical Z-scoreIsolation ForestLSTM Deep DetectorMultivariate CorrelationSeasonal DetectionDrift DetectionCausal Graph RCABlast RadiusDocker Auto-HealRedis WALMulti-Tenant IsolationOpenTelemetryRBAC EnforcementTamper-Evident Audit
Compatibility

Keep your existing monitoring stack.
Add intelligence on top.

Bring telemetry from the tools you already use. WATCHDOG adds a detection and response layer — no ripping out Prometheus, no new agents on every host.

📡 Prometheus
🔭 OpenTelemetry
🔗 Webhooks
📤 Push API
🔔 AlertManager
🐶 Datadog
🚨 PagerDuty
☁️ CloudWatch

Integration depth varies. Prometheus scraping, Push API, and webhook adapters are fully implemented. Some integrations are in active development. Contact us to discuss your specific stack.

The Problem

Incident response is still manual.
That's expensive.

Every minute of downtime costs money. Traditional monitoring alerts humans, then waits — while engineers investigate, diagnose, and fix under pressure at 3am.

Without WATCHDOG
📟Alert fires
👤Engineer wakes up
🔎Manual investigation
📜Grep through logs
🤔Hypothesize root cause
⏳Decide and act manually
✋Manual recovery
😴RCA written later (maybe)
With WATCHDOG
📡Anomaly detected automatically
📈Failure predicted before impact
🧠Root cause identified with confidence
🌐Blast radius calculated
🛡️Safety gates evaluated
⚡Autonomous remediation executed
✅Recovery verified
📋Audit trail recorded automatically
Why WATCHDOG

Four things that make
WATCHDOG different

🔍
Multi-engine detection
6 independent detection approaches run in parallel on every event — statistical, ML, deep learning, multivariate, seasonal, and drift. Not a single threshold. Not a single point of failure.
🧠
From detection to diagnosis
Failure prediction, root cause analysis, dependency topology, blast radius estimation, and change intelligence all feed into a single incident view. Anomaly detection is only the beginning.
⚡
Autonomous remediation with guardrails
Confidence gates, severity thresholds, cooldowns, rate limits, and circuit breakers ensure every automated action is evaluated before execution. Not blind automation — engineering discipline.
🔐
Built for multi-tenant environments
Complete tenant isolation at the database level, JWT authentication, RBAC with three roles, tamper-evident audit chain, and Redis WAL durability. Ready for MSP and enterprise deployment.
Who Is It For

Built for the teams
that own uptime

🛠️
DevOps / SRE Teams
Reduce alert fatigue and accelerate incident resolution. WATCHDOG handles the detection-to-remediation loop for supported incidents so your team focuses on the ones that need human judgment.
🏢
MSPs / Managed Cloud Providers
Add intelligent monitoring and autonomous remediation to your managed services offering. Multi-tenant architecture means one deployment serves all your customers with complete isolation.
🚀
Infrastructure-Heavy SaaS
Detect failures and degradation before they become customer-facing incidents. Failure prediction and capacity forecasting give you time to act rather than react.
🚀
Ready to see WATCHDOG in your environment?
Limited pilot program. Connect your existing Prometheus or push API and see real service discovery and anomaly detection in minutes. No rip-and-replace required.
Platform

One intelligence layer.
End-to-end.

WATCHDOG connects to your infrastructure, runs a multi-stage intelligence pipeline, and closes the loop with autonomous remediation and audit.

1
Ingest
2
Detect
3
Predict
4
Diagnose
5
Decide
6
Remediate
7
Verify
Step 1 — Ingest
Connect any telemetry source
WATCHDOG receives data through multiple paths. No agent required for push mode. The async batch writer flushes to PostgreSQL via Redis WAL — nothing is lost on restart.
Prometheus scraping (auto-detected endpoint type)
Batch Push API — POST /api/v1/ingest/batch
OpenTelemetry: metrics, logs, traces
Webhooks: Grafana, AlertManager, Datadog, PagerDuty, generic
Windows Exporter (CPU, memory, disk, process count)
Redis WAL — event durability across restarts
Step 2 — Detect
Six engines. One verdict.
Every event passes through six detection algorithms in parallel. Results are combined with confidence scoring. Adaptive thresholds update per-service — no manual tuning.
Statistical Z-score — deviation from rolling baseline
Isolation Forest — ML-based outlier detection
LSTM-style deep detector — sequence-aware patterns
Multivariate correlation — cross-metric relationships
Seasonal detector — time-of-day and weekly patterns
Drift detector — distribution shift over time
Step 3 — Predict
Warn before impact
Trend analysis and capacity prediction run on the anomaly signal to identify services trending toward failure before they affect users.
Failure prediction — time-to-failure estimates from current trajectory
Capacity prediction — disk, memory, connection pool exhaustion
Risk scoring — composite per-service risk assessment
ARIMA and linear regression for trend analysis
Step 4 — Diagnose
Root cause, not just symptoms
The correlation engine, dependency mapper, causal graph, and change intelligence work together to identify the most probable root cause with explainable confidence.
Correlation engine — cross-service anomaly timing
Causal graph — directed dependency relationships
Blast radius — downstream impact estimation
Change intelligence — deployment-to-incident correlation
Probability ranking — ranked root cause candidates
Step 5 — Decide
Guardrails before action
The decision engine evaluates every candidate action against safety gates before dispatch. Actions that fail any gate are blocked and logged.
Confidence threshold: minimum 65% required
Severity gate: HIGH or CRITICAL events only
Per-service cooldown: 30 seconds between actions
Rate limit: 10 actions per hour total
Circuit breaker: trips after 3 consecutive failures
Auto-Heal registration required per service
Step 6 — Remediate
Real actions on real infrastructure
WATCHDOG executes remediation via Docker SDK or systemd. Recovery time 1.4–1.7 seconds verified in testing. Every action is logged to the audit chain before execution.
Docker container restart via Docker SDK (verified)
Systemd service control as fallback
Stop, restart, scale actions
Cache flush and connection draining
Audit entry written before execution begins
Step 7 — Verify
Confirm recovery, learn from outcome
WATCHDOG monitors the service after remediation to confirm recovery. Success or failure feeds back into the model to improve future confidence scoring.
Post-action monitoring confirms service health
Outcome recorded in tamper-evident audit chain
Success/failure fed back to confidence model
Online learning improves decisions over time
Reinforcement optimizer updates action weights
Architecture

Technical architecture

How data flows through the WATCHDOG intelligence pipeline.

Infrastructure (servers, containers, services)
Telemetry / APIs (Prometheus · OTel · Push · Webhooks)
WATCHDOG Ingestion (Redis WAL + Async Batch Writer)
Detection Engines (6 parallel algorithms)
Prediction + Intelligence (trend · capacity · risk)
RCA + Topology (causal graph · blast radius · change intel)
Decision / Safety Engine (confidence gates · cooldown · rate limit)
Auto-Heal (Docker SDK · systemd · circuit breakers)
Audit + Dashboard (tamper-evident chain · real-time UI)
🔬
Want a technical deep-dive?
We're happy to walk engineering teams through the full architecture, detection algorithms, and safety model in a 30-minute call.
How It Works

From telemetry to recovery
in one pipeline

WATCHDOG runs a continuous intelligence loop. Here is what happens end-to-end.

📡
1. Connect Infrastructure
Point WATCHDOG at your Prometheus endpoint, push via the batch API, or configure webhooks. Automatic service discovery — no manual service registration required.
⚙️
2. Ingest and Normalize
Events from all sources are normalized, timestamped, and queued in Redis WAL. The async batch writer flushes to PostgreSQL every 50ms. Nothing is lost on restart.
🔍
3. Multi-Engine Detection
Each event passes through six anomaly detection engines in parallel. Results are combined with confidence scoring and severity classification.
📈
4. Failure Prediction
Trend analysis, capacity prediction, and risk scoring identify services trending toward failure and provide time-to-failure estimates.
🧠
5. Root Cause Analysis
The correlation engine and causal graph identify which service likely caused the anomaly. Change Intelligence checks if a recent deployment correlates.
🛡️
6. Safety Evaluation
Confidence threshold, severity gate, cooldown, rate limit, and circuit breaker checks all run before any action is dispatched.
⚡
7. Autonomous Remediation
Docker container restart via Docker SDK. Systemd as fallback. 1.4–1.7s verified recovery time. Every execution logged before it runs.
✅
8. Recovery Verification
Post-action monitoring confirms recovery. Success or failure feeds back into the confidence model. WATCHDOG improves with every action.
📋
9. Audit Trail
Every detection, decision, and action is written to a tamper-evident cryptographic audit chain. Each entry links to the previous via hash.
Auto-Heal

Automation with guardrails

WATCHDOG does not blindly restart services. Every remediation action passes through a multi-gate safety evaluation before execution.

1
Anomaly Confirmed
High or critical severity anomaly confirmed by multiple engines. Confidence score and severity passed to the decision engine.
2
Confidence Gate
Confidence must be ≥ 65%. Events below threshold are blocked and logged for human review.
⚡ Hard threshold: 65% minimum
3
Severity Gate
Only HIGH and CRITICAL severity events are eligible for autonomous action. MEDIUM and LOW generate alerts only.
⚡ Minimum severity: HIGH
4
Cooldown Check
30-second per-service cooldown prevents rapid repeated actions on the same service.
⚡ Cooldown: 30 seconds per service
5
Rate Limit Check
Maximum 10 auto-heal actions per hour. Circuit breaker trips after 3 consecutive failures on one service.
⚡ Rate limit: 10/hour · CB: 3 failures
6
Action Execution
Docker restart via SDK. Logged to audit chain before execution. Verified 1.4–1.7s recovery time in testing.
7
Feedback Loop
Recovery confirmed by post-action monitoring. Outcome feeds back into confidence model. WATCHDOG learns from every action.
Real Behavior — Demo Environment
✓ EXECUTED
service: payments-api
confidence: 69%
severity: HIGH
safety gates: PASSED
action: docker restart
recovery: verified 1.4s
audit: recorded
✗ BLOCKED
service: auth-service
confidence: 63%
severity: HIGH
reason: below 65% threshold
action: alert only
audit: recorded
These examples are from the WATCHDOG development environment. Not production customer data.
Supported remediation actions
docker restart docker stop docker scale systemd restart clear cache drain connections
Actions are only executed for services registered for Auto-Heal. Manual registration required per service.
Validation

Reliability and validation

Engineering validation performed in the WATCHDOG development environment. These are not production customer statistics.

40/40
Reliability tests passed
50
Concurrent servers — load test
108/s
Events/sec — 0 failures
1.4–1.7s
Verified Auto-Heal recovery
✓
WAL recovery verified
✓
Docker Auto-Heal verified
✓
Multi-tenant isolation verified
✓
RBAC enforcement verified
Engineering validation performed in the WATCHDOG development environment.
Capabilities

Everything you need.
Nothing fabricated.

Real capabilities, verified in engineering testing.

🔍
6-Engine Anomaly Detection
Statistical Z-score, Isolation Forest, LSTM deep detector, multivariate correlation, seasonal detection, and drift detection run in parallel on every event.
z-scoreisolation-forestlstmseasonal
📈
Failure Prediction
Trend analysis and capacity prediction identify services trending toward failure before they impact users. ARIMA and linear regression for time-series analysis.
arimacapacityrisk-score
🧠
Root Cause Analysis
Correlation engine, causal graph, dependency mapper, and probability ranker work together to identify the most likely root cause with explainable confidence.
causal-graphcorrelationprobability
🌐
Service Topology
Auto-discovered dependency graph shows how services connect. Blast radius estimation calculates downstream impact when a service degrades or fails.
dependency-graphblast-radius
📋
Change Intelligence
Register deployments and configuration changes. WATCHDOG automatically correlates recent changes with detected anomalies to identify deployment-induced incidents.
deploymentcorrelation
⚡
Autonomous Remediation
Real Docker restarts via Docker SDK. Systemd fallback. Confidence gates, cooldowns, rate limits, and circuit breakers on every action. 1.4–1.7s verified recovery.
docker-sdksystemdguardrails
🔒
Tamper-Evident Audit
Every detection, decision, and action is written to a cryptographic audit chain. Each entry links to the previous via hash — any modification is detectable.
crypto-chainaudit-log
👥
Multi-Tenant Platform
Complete tenant isolation at the database level. JWT authentication with RBAC: viewer, operator, and admin roles enforced at every API endpoint.
jwtrbacisolation
🔄
WAL Recovery
Redis Write-Ahead Log preserves every event. On restart, orphaned events are replayed automatically. No data loss on backend restarts or crashes.
redis-waldurability
📡
Universal Ingestion
Prometheus scraping, Push API, OpenTelemetry, webhook adapters. Supports metrics, events, logs, and traces from 15+ source types.
prometheusotelwebhooks
🤖
Self-Learning
Online learning updates detection models continuously. Reinforcement learning optimizer improves remediation decisions based on outcomes. Adaptive thresholds per service.
online-learningrl-optimizer
🏗️
Guided Onboarding
6-step setup wizard handles connection, data validation, service discovery, and Auto-Heal registration. Zero to monitored in under 5 minutes.
wizardauto-discovery
Security

Built with security
from the ground up

WATCHDOG implements enterprise security controls across authentication, authorization, data isolation, and audit. We are honest about our current certification status.

🔑 JWT Authentication
HS256 signed tokens with 24-hour expiry. Every API request authenticated. Tokens include tenant_id and role claims for authorization.
👥 RBAC
Three roles: viewer (read-only), operator (operational actions), admin (full access). Enforced at middleware layer on every request.
🏢 Tenant Isolation
Complete data isolation at the database level. Cross-tenant access returns 403. Tenant ID validated from JWT — query parameter manipulation is rejected.
⛓️ Cryptographic Audit Chain
Every action written to a tamper-evident linked chain. Each entry includes a hash of the previous entry. Modification is detectable.
🛡️ SQL Injection Protection
Middleware blocks SQL injection patterns in parameters. Parameterized queries via SQLAlchemy ORM throughout. No raw SQL string concatenation.
⏱️ Rate Limiting
Auth endpoint rate-limited to prevent brute force. Auto-Heal rate-limited to 10 actions/hour with per-service cooldowns.
🗄️ PostgreSQL + Redis WAL
All persistent data in PostgreSQL. Redis WAL provides event queue durability. Connection pooling with overflow limits.
📜 Persistent Audit Records
Every detection, decision, and remediation persisted to database. Supports incident investigation and compliance review.
🔒 Security Middleware
Request validation, tenant verification, and permission checks applied uniformly across all 104 API endpoints.
Certification Status: WATCHDOG is currently in pilot stage. Formal third-party security certifications such as SOC 2 Type II and ISO 27001 have not yet been completed. We will not make misleading compliance claims. If certification is a hard requirement, contact us to discuss our security posture and roadmap directly.
Pricing

Simple pilot pricing

We are in active pilot phase. Pricing reflects real value delivery. Final pricing depends on deployment scale and requirements.

Pilot
₹5,000/mo
Pilot pricing · billed monthly
For small teams evaluating WATCHDOG on a single environment with up to 10 monitored services.
  • Up to 10 services monitored
  • 1 tenant
  • All 6 anomaly engines
  • Failure prediction
  • Root cause analysis
  • Auto-Heal (up to 5 actions/hr)
  • Push API + Prometheus
  • 7-day audit retention
  • Community support
Business
₹15,000/mo
Pilot pricing · billed monthly
For growing teams with multiple services needing full incident intelligence and Auto-Heal.
  • Unlimited services
  • Up to 5 tenants
  • All 6 anomaly engines
  • Full prediction suite
  • Advanced RCA + topology
  • Auto-Heal unlimited
  • All ingestion sources
  • Change intelligence
  • 30-day audit retention
  • Email support
Enterprise
Custom
Negotiated · deployment-based
For MSPs, large organizations, and deployments needing dedicated infrastructure, SLAs, and custom integrations.
  • Unlimited everything
  • Unlimited tenants
  • On-premise deployment
  • Custom integrations
  • Dedicated support
  • SLA guarantees
  • Security review
  • Training and onboarding

Initial pilot pricing. Final pricing depends on deployment scale, number of monitored services, tenant count, and support requirements. We are transparent about our early-stage status.

Partner Program

Turn infrastructure monitoring
into an intelligent managed service

MSPs, DevOps consultancies, and cloud providers can package WATCHDOG as part of their managed services offering. You bring the customer relationship. We provide the intelligence platform.

1
Partner brings customer environment
You identify a customer needing better incident response. Infrastructure type doesn't matter — Prometheus, Docker, Kubernetes, Windows Server.
2
WATCHDOG connects and discovers
Setup wizard handles connection and automatic service discovery. Customer is monitored within minutes, not days.
3
Partner packages as managed service
Bundle WATCHDOG with your managed infrastructure offering. Set your own margin on top of WATCHDOG partner rates.
4
WATCHDOG provides product support
We handle product updates, bug fixes, and technical support. You handle the customer relationship.
5
Scale together
Multi-tenant architecture means one deployment serves all your customers with complete isolation and separate dashboards per customer.
💰
Revenue opportunity
Add autonomous incident response to your managed services portfolio. Set your own pricing and margin above WATCHDOG partner rates.
🏗️
Multi-tenant architecture
One WATCHDOG deployment serves all your customers. Complete tenant isolation. Separate dashboards, credentials, and data per customer.
🛠️
Technical support
We provide technical support, documentation, and training. Early partners get direct founder access and product input.
No existing partnerships are claimed. We are building our partner network from scratch. Early partners receive preferred pricing and direct technical support from the founder.

Partner Application

Demo

See WATCHDOG in action

A complete walkthrough from infrastructure connection to autonomous remediation and verified recovery.

▶
Demo video coming soon
We're recording a professional walkthrough. In the meantime, book a live demo with the founder.
1
Connect infrastructure
Point WATCHDOG at a Prometheus endpoint or configure push API. The setup wizard validates the connection and starts scraping.
2
Discover services automatically
WATCHDOG reads the metrics stream and identifies services. No manual service registration. Services appear in the dashboard within one scrape interval.
3
View telemetry in real time
Live event stream shows metrics as they arrive. Health score and anomaly count update in real time on the overview dashboard.
4
Detect anomaly across 6 engines
Watch the six detection engines flag an anomaly simultaneously. Confidence score, severity classification, and affected metric shown on the anomaly dashboard.
5
Generate failure prediction
Prediction engine shows time-to-failure estimate and risk score. Capacity prediction identifies resource exhaustion trajectory.
6
Perform root cause analysis
RCA engine shows probable root cause with confidence, correlated services, and ranked candidates. Change intelligence correlates recent deployments.
7
View topology and blast radius
Service dependency graph shows the incident source. Blast radius shows downstream services at risk. Click any node for service detail and anomaly count.
8
Evaluate Auto-Heal decision
Decision engine evaluates confidence, severity, cooldown, rate limit, and circuit breaker in real time. PASSED or BLOCKED shown with reason.
9
Execute remediation
Docker restart via SDK. Action logged to audit chain before execution. Timer starts.
10
Verify recovery
Post-action monitoring confirms service health. 1.4–1.7 second recovery verified in testing. Outcome recorded and feedback loop updated.
11
View audit trail
Complete incident record from detection to resolution. Tamper-evident cryptographic chain. Every entry timestamped and linked to the previous.
Request Pilot

Start your WATCHDOG pilot

Limited pilot program. Fill this out and we will respond within 24 hours to discuss your infrastructure and get you set up.

We respond within 24 hours. No spam, no automated sales sequences.
Documentation

Getting Started

Quick Start

WATCHDOG requires Python 3.11+, PostgreSQL, and Redis. Fastest path is Docker Compose.

1. Clone and configure

git clone https://github.com/Ayushwalunjkar77/watchdogg-intelligence cd watchdogg-intelligence

2. Start with Docker Compose

docker-compose up -d # API: :8001 · PostgreSQL: :5432 · Redis: :6379

3. Get an auth token

curl -X POST "http://localhost:8001/auth/token?\ tenant_id=acme&secret=YOUR_SECRET&role=admin"

4. Open the dashboard

http://localhost:8001/dashboard

5. Push your first event

curl -X POST http://localhost:8001/api/v1/ingest/batch \ -H "Authorization: Bearer YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "tenant_id": "acme", "events": [{"service": "payments-api", "metric": "latency_ms", "value": 2450.0}] }'

Ingestion

WATCHDOG accepts data from multiple sources. All paths end in the same intelligence pipeline.

Batch API (push mode)

POST /api/v1/ingest/batch Authorization: Bearer {token} {"tenant_id":"acme","events":[{"service":"api","metric":"latency_ms","value":340.0}]}

Prometheus scraper

POST /api/v1/setup/connect {"tenant_id":"acme","type":"prometheus","url":"http://localhost:9182/metrics","interval":15}

OpenTelemetry

POST /api/v1/ingest/otel/metrics POST /api/v1/ingest/otel/logs POST /api/v1/ingest/otel/traces

Webhooks

POST /api/v1/ingest/webhook/{source} # source: grafana | alertmanager | datadog | pagerduty | generic

Authentication

WATCHDOG uses JWT authentication. All API calls require a Bearer token.

Get a token

POST /auth/token?tenant_id=acme&secret=YOUR_SECRET&role=admin # Roles: viewer | operator | admin | customer # Tokens expire after 24 hours

RBAC permissions

viewer — read-only access to all data

operator — read + write operational actions

admin — full access including tenant management

Onboarding

The WATCHDOG setup wizard handles tenant configuration, infrastructure connection, and service discovery.

Setup wizard (browser)

http://localhost:8001/setup # 6-step wizard: Connect → Ingest → Discover → Auto-Heal → Validate → Done

Programmatic setup

POST /api/v1/setup/start {"tenant_id":"acme"} POST /api/v1/setup/connect {"type":"prometheus","url":"..."} GET /api/v1/setup/validate?tenant_id=acme POST /api/v1/setup/autoheal

API Reference

WATCHDOG exposes 104 REST endpoints. Interactive docs at /docs when backend is running.

Core endpoints

GET /health GET /api/v1/pipeline/status GET /api/v1/dashboard/{tenant_id} GET /api/v1/anomaly/list POST /api/v1/anomaly/detect GET /api/v1/incidents PATCH /api/v1/incidents/{id} POST /api/v1/rca/analyze GET /api/v1/topology/graph GET /api/v1/topology/blast-radius/{svc} GET /api/v1/autoheal/history POST /api/v1/changes/register GET /api/v1/audit GET /api/v1/compliance/soc2

Auto-Heal Configuration

Register services

POST /api/v1/setup/autoheal {"tenant_id":"acme","services":["payments-api","auth-service"]}

Default thresholds

confidence_threshold: 0.65 # 65% minimum severity_minimum: "high" # high or critical only cooldown_seconds: 30 rate_limit: 10 # per hour circuit_breaker: 3 # trips after 3 failures

Docker Deployment

version: '3.8' services: api: build: . ports: ["8001:8001"] environment: - DATABASE_URL=postgresql://... - REDIS_URL=redis://redis:6379 - WATCHDOG_SECRET=your-secret depends_on: [postgres, redis] postgres: image: postgres:15 environment: POSTGRES_DB: watchdog_db POSTGRES_PASSWORD: secure-password redis: image: redis:7-alpine

Environment variables

DATABASE_URL=postgresql://user:pass@host:5432/db REDIS_URL=redis://localhost:6379 WATCHDOG_SECRET=your-api-secret WATCHDOG_PORT=8001
About

Built by an engineer
who got paged too many times

WATCHDOG Intelligence started from a simple frustration: monitoring tools tell you when things break, but they don't fix anything. Every incident still requires a human to wake up, investigate, diagnose, and remediate — manually, under pressure.

The goal was to build something that could handle the routine incidents autonomously, so engineers could focus on the ones that actually need human judgment.

WATCHDOG is early-stage. It's technically real — working backend, real anomaly detection, real Auto-Heal, real multi-tenant isolation. It doesn't have production customers yet, but it's ready for them.

🔍 Honest about what we are
Early-stage. No Fortune 500 customers. No SOC2. A working product that solves a real problem.
🛡️ Safety over speed
Auto-Heal has confidence gates, cooldowns, rate limits, and circuit breakers. We'd rather block an action than cause an incident trying to fix one.
📋 Auditability by design
Every detection and remediation action is logged to a tamper-evident chain. You should always be able to see exactly what WATCHDOG did and why.
AW
Ayush Walunjkar
Founder — WATCHDOG Intelligence
Instrumentation Engineering student at SPPU, Pimpri-Chinchwad / Pune. Built WATCHDOG Intelligence as a full-stack AIOps platform — backend, intelligence pipeline, dashboard, security, and onboarding — from scratch.

WATCHDOG is not a class project. It's a commercial product built to replace the incumbent monitoring + manual response workflow with autonomous incident intelligence.
Current Status: WATCHDOG is in active pilot phase. The backend is production-grade in architecture and testing. Seeking first 5–10 pilot customers and evaluating accelerator and early-stage funding opportunities.