B2B SaaS · Travel-Tech Under NDA Under NDA · anonymized

Dev headcount cut from 8 to 3 engineers.
Plus support that fixes the product itself.

A tech platform with thousands of active users. Single API, complex infrastructure underneath. Before us, 80% of the dev team's time went into support. After: an AI copy of the dev department runs 24/7, and live support on the site diagnoses and ships fixes itself via a tight loop with engineering agents.

8 → 3
engineers
~$108K
saved per year
24/7
support, no days off
~2 min
from complaint to fix
Before

8 engineers drowning in support.

A bespoke module built for this client

Support that fixes the product itself.

On the platform's site — a live support chat. In tone and response time, indistinguishable from a human. Behind it: a tight loop of 4 agents — Support, Bug-fixer, Code Review, and DevOps. User complains → Support diagnoses → hands the task to Bug-fixer → the code goes to review → DevOps ships it to production. Time from complaint to fix: usually 2–5 minutes.

Mai ROUTER · SEES EVERYTHING booking.app Site OK 200 · 89ms booking.app ! Error 500 booking timeout booking.app Fixing... deploying patch "Site is down!" error 500 · booking AGENT 1 · SUPPORT "Site won't load" Looking into it… Reproducing the bug… diagnoses · 8s AGENT 2 · FIX booking.py 12 def book(req): 13 - timeout=5 13 + timeout=30 14 + retries=3 15 return book_ PR + tests · 12s AGENT 3 · CODE REVIEW PR #4821 fix(booking): timeout + retries tests (42/42) security · OK approved approved · 4s AGENT 4 · DEVOPS $ kubectl rollout build ━━━━━━━━━━ 100% tests ━━━━━━━━━━ 100% canary ━━━━━━━━━━ 100% → production · LIVE auto-rollback · 6s loop repeats 24/7 Site works again ~ 2 min from complaint Mai Router booking.app Site OK 200 · 89ms booking.app ! Error 500 booking timeout booking.app Fixing... deploying patch "Site is down!" AGENT 1 · SUPPORT Support diagnoses · 8s AGENT 2 · FIX Fix PR + tests · 12s AGENT 3 · CODE REVIEW Code Review approved · 4s AGENT 4 · DEVOPS DevOps auto-rollback · 6s loop repeats 24/7 RESULT Site works again ~ 2 min from complaint
1

User writes into the chat

Live support on the platform's site. No ticket forms — just a normal conversation.

2

Support agent diagnoses

Tone and timing indistinguishable from a human. In parallel — checks logs, reproduces the bug, locates root cause.

3

Task goes to Bug-fixer

If the bug is confirmed, the engineering agent picks it up. Finds the fix, writes the code, opens a PR with tests.

4

Auto-review + deploy

The code-review agent checks quality and security. The DevOps agent ships to production with automatic rollback on failure.

5

User gets a reply

"Done, please check." Typical turnaround: 2–5 minutes. No engineer paged, no on-call nights, no escalations.

AI copy of the dev department

6 server-side agents instead of 5 engineers.

Every function of the dev department — a separate agent with its own permissions and its own context. A dedicated server per client: code and IP never cross paths with anyone else.

Server-side agent What it does
Platform support Monitoring, ticket responses, incident triage 24/7. Live chat on the site.
Bug-fixer Bug analysis, root cause investigation, writing fixes, PRs to review with tests.
Feature dev Ships small features, tests, documentation. Strategy stays with humans.
Integrations Hooks up new external APIs to the platform's unified format.
Code review Reviews PRs from the remaining 3 engineers. Quality and security checks.
DevOps / releases Deploys, monitoring, rollbacks, incidents. Auto-rollback when tests fail.
Financial impact

Numbers from 3 months.

The remaining 3 engineers now work on strategic projects: new products, market expansion. The AI team absorbs support and operational work.

8 → 3
engineering headcount reduction
~$9K
saved per month
~$108K
saved per year
< 1 year
system payback
Effects

Beyond the money.

Effect Impact
Feature speed Hours, not weeks. The "idea → production" cycle is compressed by an order of magnitude.
24/7 uptime Incidents handled overnight, no "morning triage".
Strategy unblocked 3 devs on new products, not firefighting.
Scalability New client ≠ more workload.
Code quality AI review raises the bar. Fewer regressions.
Isolation: one dedicated server runs the client end to end. Platform code and customer data live only inside that perimeter. No overlap with any other S.V.I. client — not in training, not in logs, not in backups.

Same situation in your company?

If you run a tech platform and your dev team is drowning in support — we'll build the same loop on top of your stack.

Talk to Mai See HandOfHands →