3600LABS / SELECTED WORK · 47 SHIPPEDCASE STUDIES · ANONYMIZED · 2024 – 2026
◆ WORK / SHIPPED SYSTEMS / 47 TOTAL

Shipped systems.
Real outcomes.

Names anonymized - the work isn't. Numbers measured, not modeled. If a case study sounds relevant, we'll send you the named version under NDA after a discovery call.

47
Systems shipped
23
Clients
12
Industries
9
FDE deployments
78%
Retainer renewal
CASE 01
CLIENT_ID: SVC-D2C-08
INDUSTRY
D2C services · $5M ARR
ENGAGEMENT
AI Agent Sprint + FDE · 3 weeks
TEAM
1 SE + 1 FDE on-site · 5 days
LAUNCHED
November 2025
RAGWhatsAppTool-use
AI · CUSTOMER SUPPORT

An AI assistant that resolved 72% of customer tickets in 21 days.

A D2C services brand was buried under repetitive WhatsApp + email queries: order status, shipping windows, refund policies. Their 6-person support team was drowning, and queries grew faster than headcount.

// PROBLEM

14 hours of operator time per week, every week, answering the same 80% of questions. Customers waited 6–9 hours for a response. NPS was sliding.

// SOLUTION

FDE spent 5 days on-site reading actual conversations. We shipped a RAG agent trained on FAQs, policies, order data, and 18 months of past chats - with hard rules for escalation. Human handoff on anything ambiguous.

// ARCHITECTURE

Anthropic Claude + pgvector RAG + WhatsApp Cloud API + Zendesk handoff. Audit log on every reply, daily review meeting for the first 30 days.

// OUTCOME

L1 tickets stopped landing in human queues. Support team moved to higher-value retention work. Customer-side latency went from hours to seconds.

RESPONSE TIME
−84%
AUTO-RESOLVED
72%
LAUNCH SPEED
21 days
CASE 02
CLIENT_ID: LOG-OPS-12
INDUSTRY
Logistics · 200 fleet
ENGAGEMENT
Internal Tool Build + FDE · 5 weeks
TEAM
2 engineers · 1 FDE · 8 days on-site
LAUNCHED
January 2026
RealtimeRBACSLA
INTERNAL · OPS DASHBOARD

Replaced 6 spreadsheets and 3 SaaS subscriptions with one dashboard.

A growing logistics company was running operations on Google Sheets, two WhatsApp groups, three SaaS tools, and a lot of phone calls. Nobody could see the same number. SLA breaches were guesswork.

// PROBLEM

Dispatchers updated 6 spreadsheets manually after every shipment. The COO couldn't get a real number for "shipments at risk" without calling someone. Finance reconciled at end-of-month - too late.

// SOLUTION

FDE shadowed dispatchers for 8 days, then we built a real-time operations dashboard. Role-based access (driver / dispatcher / COO / CFO), SLA alerts, automated client notifications, full audit trail.

// ARCHITECTURE

Next.js + Postgres + Supabase Realtime + Twilio + an event bus syncing to existing TMS via webhooks. Hosted on the client's GCP.

// OUTCOME

Manual updates collapsed. SLA breaches dropped 61% in the first quarter. They cancelled 3 SaaS subscriptions in month two. The CFO got real-time visibility into receivables for the first time.

MANUAL UPDATES
−92%
SLA BREACHES
−61%
SAAS COST SAVED
$450/mo
CASE 03
CLIENT_ID: SAAS-MVP-04
INDUSTRY
Vertical SaaS · Property mgmt
ENGAGEMENT
MVP Build · 7 weeks
TEAM
1 SE + 2 engineers + 1 designer
LAUNCHED
March 2026
Multi-tenantStripe-readyNext.js
MVP · VERTICAL SAAS

Idea to investor-ready demo in 49 days.

A solo founder had validated demand for a niche property-management SaaS in the Indian market. No technical team. Investor demos booked in 8 weeks.

// PROBLEM

Founder couldn't hire engineers fast enough to ship a demo. Most agencies quoted 4 months, twice his budget. He needed working software in his hands - not a Figma file.

// SOLUTION

We scoped the MVP down to 3 jobs-to-be-done. Designed and built a multi-tenant SaaS with auth, role-based access, billing-ready architecture, admin panel, and an analytics dashboard.

// ARCHITECTURE

Next.js + Prisma + Postgres + Clerk auth + Stripe-ready billing + Vercel deploy. Multi-tenant via tenant_id row scoping, clean schema for future scale.

// OUTCOME

Demo-ready in week 6. Founder showed real software to investors, not a slide deck. Closed his seed round end of Q1 with 4 pilot customers already paying.

TIME TO MVP
49 days
PILOT CUSTOMERS
4 paying
SEED RAISED
Q1 closed
CASE 04
CLIENT_ID: FIN-AUTO-03
INDUSTRY
Professional services · Tax + audit
ENGAGEMENT
Automation Sprint · 12 days
TEAM
1 engineer · remote
LAUNCHED
February 2026
OCRMultimodalSheets
AUTOMATION · DOC INTELLIGENCE

Saved 32 hours/week of invoice processing for a tax firm.

A mid-sized accounting firm received 600+ vendor invoices per week across email, WhatsApp, and physical scans. Three full-time staff did nothing but data entry.

// PROBLEM

Manual data entry from invoices into Tally was the bottleneck of their accounting practice. Errors compounded. Junior staff burned out. They couldn't take on new clients without hiring.

// SOLUTION

Built an invoice ingestion pipeline: email + WhatsApp + dropbox → multimodal LLM extracts structured data → human-review queue for low-confidence rows → auto-post to Tally via API.

// ARCHITECTURE

Gemini multimodal for extraction (per-page confidence scoring), n8n for the workflow, Supabase as queue + audit log, a small web UI for the review step.

// OUTCOME

Three accounts assistants moved to client-advisory work. The firm took on 14 new clients in the next quarter without hiring. Cost: $1.4k one-time + $50/mo in API costs.

HOURS SAVED
32/week
EXTRACTION ACC.
96.4%
NEW CLIENTS
+14 in Q1
CASE 05
CLIENT_ID: HC-PT-FDE-01
INDUSTRY
Healthcare · Multi-clinic chain
ENGAGEMENT
FDE Program · 4 weeks on-site
TEAM
2 FDE on-site · 1 SE remote
LAUNCHED
April 2026
★ FDEEMRHL7
★ FDE PROGRAM · HEALTHCARE

Cut patient check-in time by 68% across 9 clinics.

A multi-clinic chain had a patient bottleneck at the front desk. Three different EMR systems across locations, paper intake forms, manual insurance verification. Wait times: 22 minutes.

// PROBLEM

You can't fix this from a Zoom call. Every clinic ran slightly differently. The previous "digital transformation" vendor failed because they shipped a generic check-in app that ignored real workflows.

// SOLUTION (FDE)

Two FDEs deployed for 4 weeks - one week at each of the top-4 clinics. They watched check-ins, talked to receptionists, found 11 distinct workflows where there should have been 1. Then built it.

// ARCHITECTURE

React Native staff app + patient self-check-in tablet + insurance API integration + HL7 bridge to the 3 EMRs. Offline-first. Designed around the actual reception desk geometry.

// OUTCOME

Wait time dropped from 22 to 7 minutes. Staff adoption was 94% in week one - because the FDE had already gotten buy-in face-to-face. Rolling out to 14 more locations in Q3.

WAIT TIME
−68%
STAFF ADOPTION
94% wk1
LOCATIONS LIVE
9 → 23
// MORE WORK · LIGHTNING ROUND

42 more shipped systems.

Most of our work is under NDA. We'll share named case studies after a discovery call.
CASE 06 · D2C
Returns automation

Cut return-processing time from 4 days to 14 hours for a 200-SKU brand.

CASE 07 · EDTECH
AI tutor MVP

Adaptive math tutor for grades 6–10. Built in 6 weeks, 3,400 weekly users.

CASE 08 · LEGAL
Contract review copilot

RAG-based clause review for an in-house team. 22 hours/lawyer/week saved.

CASE 09 · RETAIL · ★ FDE
Inventory tablet

FDE in 4 retail stores for 2 weeks. Built the inventory app store managers actually want.

CASE 10 · MEDIA
Editorial CMS

Custom CMS for a digital publication. 12 editors, 6× faster than their old tool.

CASE 11 · MFG
Quality dashboard

Real-time defect tracking across 3 lines. Replaced clipboards with iPads.

CASE 12 · FINTECH
KYC pipeline

Multimodal KYC verification - drivers' license + selfie + GST cross-check.

CASE 13 · NGO
Field-worker app

Offline-first survey app for 140 community health workers across 6 districts.

+ 34 MORE
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