AI product engineering for ambitious SaaS teams
Build AI-enabled software your customers can actually trust.
LaunchStacks designs and delivers production AI systems, data platforms, and cloud-native SaaS for healthcare, fintech, and growing technology companies — from first release through long-term scale.
Healthcare · Fintech · Trust & Safety · Data-intensive SaaS
Shipped by LaunchStacks — live in production today
- ChainAbuse
- Divergence Neuro
- Credora
- Racing Manager
- Recognize
- Image3D
- Kauai
- Pure App
- years shipping software
- 12+
- products delivered over that time
- 50+
- payment volume processed on platforms we built
- $100M+
- end users reached across those products
- 1M+
50+ products delivered across 12+ years. Companies pivot, get acquired, and sunset products — the names above are the platforms you can still open today. See all the work.
What we build
Four disciplines, one production standard
Featured case study
ChainAbuse: threat intelligence for reporting and investigating crypto scams
Scam reports arrive as unstructured text at high volume, quality varies wildly, and the same fraud campaign surfaces across hundreds of submissions. Turning that stream into signals investigators can act on is the entire product.
- reports filed monthly
- 50K+
- of malicious wallets flagged
- 1000s
Industry expertise
Domains where correctness is the product
Healthcare
Clinical workflows, healthcare payments, and research platforms built for sensitive data.
- Clinical and research workflows
- Healthcare payments
- Permissions and auditability
- Reliable integrations
Selected work: Hamilton Pay · Topography Health · Divergence Neuro
Fintech
Payment systems and transaction workflows where reliability is the product.
- Payment and transaction systems
- Risk controls
- Secure architecture
- Financial data integrity
Selected work: Hamilton Pay · Credora
Trust & Safety
Abuse reporting, investigation workflows, and risk intelligence at volume.
- Abuse reporting pipelines
- Investigation and moderation workflows
- Risk intelligence
- Fraud and threat signals
Selected work: ChainAbuse
Data-Intensive SaaS
Complex workflows, analytics, search, and high-volume integrations.
- Complex product workflows
- Analytics and internal platforms
- Search and automation
- High-volume integrations
Selected work: Spoken · Work Well Together · Timz
Why LaunchStacks
The difference between shipped once and running for years
Senior engineers, no bait-and-switch
The people on your kickoff call write the code. No account managers translating, no junior placeholders billed as seniors, no rotating contractors.
AI treated as production engineering
Models are dependencies like any other: evaluated before launch, monitored after, capped on cost, and backed by fallback paths for the day a provider goes down.
Fluent in regulated and sensitive domains
Payments, clinical workflows, and trust & safety systems — we build for the audits, permissions, and failure costs those domains carry.
Built to be maintained, not just shipped
Typed APIs, tests that catch real bugs, structured logs, and runbooks. A new engineer is productive in days; an acquirer's diligence team finds what it expects.
How we deliver
A process that produces artifacts, not status meetings
- 01Product brief
Discovery
A short call and a written brief. Goals, users, success criteria, and any data or compliance considerations — captured before anyone estimates anything.
- Goals, users, and success metrics in writing
- Sensitive data, integrations, and regulatory context reviewed upfront
- Risks named at the start, not discovered mid-build
- 02System design & milestone plan
Architecture
System design, milestones, and acceptance criteria agreed before the first sprint. Written down, so there are no black-box estimates.
- Architecture diagram with the rationale for each technology decision
- Milestone plan with weekly demo dates
- Acceptance criteria for every deliverable
- 03Weekly staging demos
Build
Short iterations with code review on every change and a staging environment you can share with stakeholders. Observability wired in from the first deploy.
- Weekly demo on staging — your domain, your real data shape
- Structured logs, traces, and alerts from the start
- Migrations rehearsed against production-shaped data before they ship
- 04Runbooks & monitoring
Launch & operate
Staged cutover with monitoring and runbooks handed to your team — then the partnership most clients continue: roadmap work and platform health, month after month.
- Staged rollout with a rehearsed rollback path
- Incident runbook and on-call drill before go-live
- 30-day stabilization, then a smooth handoff to ongoing partnership
Selected work
More systems, examined properly
Customer outcomes
Measured outcomes, not borrowed adjectives
$100M+
in annual healthcare payments reconciled automatically
Hamilton Pay practices stopped hand-matching processor exports to patient accounts.
From the case study →50K+
scam reports processed every month
ChainAbuse turns unstructured victim reports into wallet-level intelligence investigators act on.
From the case study →1000+
users receiving real-time neurofeedback
Divergence Neuro streams clinical-grade biosignals from headset to browser in under a second, at 98% uptime.
From the case study →
Tell us what you are building
Share your product, stage, and constraints. We respond within one business day with an honest read on fit — and a concrete next step if there is one.