We’ve digitized law firms and shipped production legal software end-to-end. Now we bring those patterns to US mid-market firms in 8 weeks.
Stanford-engineered, eval-disciplined production AI. Validated by the ABS & Co. engagement and 18 months operating Casetrack. Start with a $15K AI Readiness Audit.
ABS & Co.
Digitized end-to-end
Brand, search, operational substrate, and eval-disciplined AI surfaces — our primary legal-vertical reference.
18 months
Operating production legal AI
Casetrack ran in production handling real matters for real attorneys. Sunset 2026 to refocus on services.
NASA · Sequoia · Stanford
Credentials investors and GCs recognize
Stanford MS&E founder · Sequoia InSITE Fellow · NASA Artemis subcontractor · Savaree → Careem exit.
What ‘shipped, evaluated, operated’ looks like in production.
Our Work
Three of the four agent templates we deploy
Each one is a productized 8-week build. Each one has shipped before.
Intake triage
New-matter intake routed, deduped, and conflict-checked by an agent before it ever hits an attorney inbox. Override band published; eval harness live from week one.
- ~3 weeks per surface, eval-disciplined
- Override band: 8–12% of cases routed for human review
Doc review assist
First-pass review on contracts, discovery, and diligence — citations rendered inline, attorney scans and approves or escalates in 30 seconds.
- ~4–6 weeks to production
- Override band: 15–20% surfaced for attorney review
Conflict-check resolution
Conflict-of-interest queries resolved against the firm’s own historical matter graph — explainable, auditable, and faster than the existing manual workflow.
- ~3–4 weeks to production
- Override band: 5–10% requiring partner sign-off
Experts in every aspect of the product lifecycle
Whether you’re a Fortune 500 or a startup in stealth mode — we give our clients the creative, technical, and business talent they need to succeed.
Cloud & AI Integration
Adopt cloud and AI seamlessly to gain agility.
Intelligent Automation
Replace manual processes with precision.
Customer Experience Redefined
Turn buyers into advocates with AI-driven insights.
Stanford-engineered. Production-shipped. Investor-recognizable.
Qasim Zafar
Founder & CEO
Stanford MS&E
Management Science & Engineering researcher
Sequoia InSITE Fellow
Sequoia Capital fellowship for early-stage founders
NASA Artemis subcontractor
Product manager — Lunar Gateway program
Savaree → Careem exit
Founding-team operator experience
18 months of production legal software
Built and operated Casetrack (sunset 2026)
Stanford MS&E researcher and Sequoia InSITE Fellow who founded AppRocket in 2017. Has shipped production AI for NASA Artemis (Lunar Gateway), digitized law firms end-to-end, and previously built and operated Casetrack, a production legal-software product (sunset 2026 to focus on services).
They were able to turn around an entire platform within 6 weeks. Kudos to their responsiveness and speed!
Our relationship is more of a transparent partnership where we talk about how we can be successful together and don't have misaligned expectations
Three productized tiers
Audit, Implement, Operate. Public pricing. No decks-required qualifying call.
AI Readiness Audit
$15,000 · 2 weeks
Three prioritized AI deployments with ROI math, an eval framework template, and a 12-month roadmap. Founder-led, vendor-neutral.
Learn more →AI Implementation
$80–250K · ~8 weeks
Production AI built against an eval harness from day one. One of four agent templates we have deployed before.
Learn more →ModelOps Retainer
$8,000/mo · ongoing
Eval drift, model swaps, incident response, and quarterly capability upgrades — production AI kept in production.
Learn more →Awards & Recognition
Our Blog
Strategy
We sunset Casetrack to focus where our leverage is highest. Here is what 18 months of running production legal AI taught us.
Casetrack was sunset in April 2026. Sunset is not failure — it is focus. The lessons from 18 months operating production case-management software in front of real attorneys are now powering AppRocket's services-only legal-vertical practice. Here is the honest story.
Delivery
Why 90 days is the right cadence for AI delivery
Three-month engagement cycles retire risk faster than any other rhythm we have tried. Here is why that shape holds up even as projects get bigger.
Engineering
Building RAG that actually works in production
Most retrieval-augmented generation systems look great in demos and fall apart in production. Here are the decisions that separate the two.
Ready to Scale with Precision?
Stop cobbling together piecemeal tools. Partner with AppRocket for AI that grows with your ambitions.