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Alpha Program • Early Access

Stop Waking Up at 3 AM
for Query Spikes.

Solanica AI Copilot (Alpha) automates the tuning, debugging, and indexing tasks that keep your SREs underwater. Built on OpenEverest.

⚠ INCIDENT DETECTED Time: 03:14 AM Service: orders-db p99 latency: 8.4s CPU: 94% AI ANALYZE Copilot Analysis Sequential scan on orders Missing index: created_at Estimated improvement: 78% CREATE INDEX CONCURRENTLY idx_orders_created_at ON orders(created_at); AUTO-FIX ✓ RESOLVED Time: 03:16 AM p99: 240ms CPU: 34%
2-minute mean time to resolution
Suggestions, not "yolo" changes
Your data never leaves your VPC

Choose Your Pain Point

We built this for engineers who are drowning in database ops. Select the problem that keeps you underwater—and see how Copilot eliminates it.

Emergency Debugging

CRITICAL

"Why is my p99 spiking right now?"

The Copilot Action: Instant root cause analysis. Copilot scans query plans, lock waits, and replication lag in real time—then pinpoints the bottleneck and suggests the fix.

$ /analyze-spike --severity=p99
→ Sequential scan on orders (2.1M rows)
→ Suggested fix: Add partial index
Resolution Time ~2 minutes

Performance Bloat

HIGH

"Our queries are slow, but we have no idea which indexes to add—or which to remove."

The Copilot Action: Automatic index suggestions and redundant index cleanup. Copilot analyzes your query patterns and generates CREATE INDEX statements—or drops the ones that are never used.

$ /optimize-indexes --table=orders
→ Found 3 unused indexes (costing 840MB)
→ Recommend adding: idx_user_status
Latency Improvement Up to 78%

Configuration Drift

MEDIUM

"We copy-pasted postgresql.conf from StackOverflow three years ago. Is it still optimal?"

The Copilot Action: Real-time tuning of postgresql.conf or my.cnf based on live traffic. Copilot monitors your workload and suggests configuration changes specific to your usage pattern.

$ /tune-config --workload=oltp
→ shared_buffers: 8GB → 16GB
→ work_mem: 4MB → 32MB (query boost)
Throughput Gain ~40% avg

Scaling Anxiety

PROACTIVE

"We don't know we need more nodes until we get OOM killed."

The Copilot Action: Predictive scaling. Copilot forecasts resource exhaustion before it happens, giving you a 48-hour warning to provision additional nodes or optimize queries.

$ /forecast-resources --horizon=7d
⚠ Memory exhaustion in ~36 hours
→ Recommend: Scale to 3 nodes
Early Warning 48 hours

See It In Action

This is how your team will interact with Copilot. Natural language commands in your terminal or dashboard—no manuals, no black boxes.

solanica-copilot@production
Connected
user@prod $ /analyze-slow-queries
Analyzing OpenEverest telemetry...
Found a sequential scan on orders table (2.1M rows scanned)
Query execution time: 8.4s → Adding a partial index will reduce this to ~240ms
Suggested Fix Copy
CREATE INDEX CONCURRENTLY idx_orders_created_at
ON orders(created_at)
WHERE status = 'active';
Want me to generate the Kubernetes manifest to apply this change?
user@prod $ Yes, generate manifest
Generating Kubernetes Job...
index-job.yaml Apply to cluster
apiVersion: batch/v1
kind: Job
metadata:
  name: create-orders-index
  namespace: solanica-db
spec:
  template:
    spec:
      containers:
      - name: postgres-index
        image: postgres:16
        command:
        - psql
        - -c
        - "CREATE INDEX CONCURRENTLY..."
      restartPolicy: OnFailure
Manifest saved to ./solanica-fixes/index-job.yaml

Context-Aware Analysis

Copilot reads your OpenEverest telemetry, query logs, and replication metrics—not just generic AI training data.

Approve-First Workflow

Every suggestion is a proposal. Copilot never applies changes to production without your explicit confirmation.

Instant Code Generation

From SQL indexes to Kubernetes manifests—Copilot generates production-ready YAML and SQL in seconds.

How It Actually Works

Engineers fear AI because it's opaque. We built Copilot to be transparent, safe, and respectful of your data sovereignty.

Context-Aware Intelligence

Copilot reads your OpenEverest telemetry—query execution plans, replication lag metrics, index usage statistics, and lock wait events. It's not just an LLM with generic database knowledge; it's trained on the actual state of your production environment.

Data Sources:
  • pg_stat_statements (query patterns)
  • OpenEverest metrics API (replication, failover)
  • Pod resource usage (CPU, memory, I/O)
  • Slow query logs (real-time)

Approve-First Workflow

Every action is a proposal, not an execution. Copilot generates SQL statements, Kubernetes manifests, and configuration changes—but it never applies them automatically. You review, approve, and deploy.

1 Copilot analyzes issue
2 Generates fix
3 You approve
4 Applied to prod
No "yolo" changes. Ever.

Your Data Never Leaves Your VPC

Copilot runs as a sidecar container in your Kubernetes cluster. Your database schemas, query patterns, and telemetry data stay within your infrastructure. We don't train our models on your proprietary data.

YOUR VPC Kubernetes Cluster Database Pod Copilot Sidecar Reads telemetry Internet / Cloud ❌ No data transfer Only model updates (encrypted)
Zero-trust architecture. Your schemas stay private.

Under the Hood

LLM Foundation
Fine-tuned on database operations, query optimization, and Kubernetes patterns
Telemetry Integration
Real-time ingestion of metrics from OpenEverest, Prometheus, and native DB stats
Code Generation
Produces idiomatic SQL, Kubernetes YAML, and shell scripts ready for review
Safety Guardrails
Read-only by default; writes require explicit human approval

Early access - Alpha feature
Ready to Stop Fighting
Database Fires?

Join the alpha program and get early access to Solanica AI Copilot. Help us build the tool that makes database operations boring again.
Book a meeting
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Book a meeting with a team.

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