Tech debt,
handled.
Knowledge Graph
Profiles the codebase — structure, impact, complexity and composes the data into a comprehensive, continuously-updated graph, reducing token burn.
Directed AI
Analyzes the graph, plans workstreams and directs a coding AI to write and re-check the code.
payment-service✓ Ran today
☍ PR opened — jackson-databind · 14m ago
order-apiPending◌ Scanning...
auth-gateway✓ Ran today
✓ All up to date · 6h ago
Lights-out Automation
Wires into the build pipeline, triggered by dependency changes — debt never accrues again.
IMPLEMENTATION
Upgrade jackson-databind
payment-svc◌ In progressBump log4j to 2.24
auth-gateway◌ In progress✓ CompletedPUSH
Bump log4j to 2.24
auth-gateway◌ In progressPR READY
Upgrade spring-core
order-api✓ CompletedBump log4j to 2.24
auth-gateway✓ CompletedThe Impact
Weeks become minutes. Months become hours.
Single-line change
Before1 day
With Lineai15 min
Major library upgrade
Before1 week+
With Lineai45 min
Framework upgrade
Before8 weeks
With Lineai5h 18m
Measured on real upgrade tasks. "Before" reflects typical human developer effort for the equivalent work.
What that speed is worth
Single-line change
Before$960
With Lineai$30
Major library upgrade
Before$4,800
With Lineai$90
Framework upgrade
Before$38,400
With Lineai$640
The same three upgrades, priced at fully-loaded senior-engineer time (~$120/hr). Lineai turns days of labor into saved dollars.
Reclaimed capacity
Across a full upgrade backlog this compounds: ~20% of a 20-person team's engineering budget — $1M+ per year — redirected from dependency debt to product.
Only Lineai
closes the loop
Capability
Dependabot / Renovate
Moderne / OpenRewrite
AI coding assistants
Lineai
Detects outdated dependencies
●
◐
—
●
Codebase-wide knowledge graph
—
◐
—
●
Fixes breaking changes
—
◐
◐
●
Autonomous, multi-step workstreams
—
—
◐
●
Recovers from build failures
—
—
◐
●
Lights-out, no prompt engineering
—
—
—
●
● = full · ◐ = partial · — = absent