AI applications built to
ship at speed.
We design and ship full-stack AI applications — agentic backends, real-time interfaces, model-agnostic architecture — delivered to production in 6–12 weeks with 100% code ownership.
6–12w
from discovery to production deployment
Full-stack
engineering — front-end, back-end, AI layer
99.9%
uptime SLA target on all production deployments
100%
source code & IP ownership from day one
Most AI product ideas die in development. Before they ever reach users.
Building AI applications is not the same as building software. The infrastructure, architecture, and AI layer decisions made in week one determine whether you ship in 12 weeks or 12 months.
8–14 mo
average time for an enterprise to ship an AI product in-house — Acsenix ships in 6–12 weeks
70%
of in-house AI products are rebuilt within 18 months due to architecture decisions made under deadline pressure
4×
more expensive to fix architectural problems in production than to design them correctly at the start
58%
of AI product initiatives fail to reach production due to underestimated infrastructure and integration complexity
Six engineering capabilities
that make AI products production-ready.
Full-Stack AI Product Engineering
Front-end, back-end, AI layer, vector store, and infrastructure — designed and deployed as one cohesive system. No handoffs between fragmented teams. One accountable delivery.
End-to-end deliveryDiscovery to deployment in 6–12 weeks.
Every phase has a defined deliverable you can hold us to. No vague milestones. No scope creep.
Product Architecture
Weeks 1–2We define the full system architecture before writing a line of code: AI layer design, data flows, API contracts, infrastructure choices, and the rollout strategy. Every decision is documented.
Architecture document + API contract + infrastructure spec
AI Layer Design
Weeks 2–3We design the intelligence layer: model selection, RAG configuration, prompt system, agent architecture, memory model — and validate it against your acceptance criteria on real inputs before build begins.
AI layer spec + model selection rationale + prompt system design
Build & Integrate
Weeks 3–9We build every layer — AI backend, product APIs, and front-end — in weekly sprints with demos on real data. Integration testing runs continuously so nothing breaks silently across layers.
Working product + integration test suite + weekly sprint demos
Launch with Observability
Weeks 10–12We deploy to production with performance monitoring, AI output quality logging, error alerting, and staged rollout capability — so you can launch confidently and iterate safely.
Production deployment + monitoring + runbooks + team training
Built for your industry's specific AI product needs.
AI copilot features embedded in existing products with streaming UX and context awareness
Intelligent search transforming keyword queries into semantic retrieval across product data
AI-powered onboarding personalizing product flows based on user role, behavior, and stated goals
Recommendation engines learning from in-product behavior to surface relevant content and actions
Real systems. Real results.
“A production-ready AI system in 6 weeks — not the 12-month internal estimate.”
Meridian's operations team needed an AI-powered reconciliation product that could process 4,000+ monthly invoices across 12 entities with full audit trail and exception handling. Their internal estimate was 12 months. We delivered a production-grade, full-stack AI application in 6 weeks — complete with a real-time processing dashboard, exception management interface, and integration with their existing ERP.
87%
reduction in processing time after AI product launch
— Laila Ostrovsky, Head of Operations
Shipped in weeks. Built to last. Yours forever.
Unlike internal teams that take 12 months or offshore shops that cut corners on architecture — we ship full-stack AI products in 6–12 weeks with model-agnostic design, production observability, and code that is entirely yours.
Internal dev teams
Months to ship. Rebuilt in 18.
- 8–14 months to production average
- AI architecture learned under pressure
- Single model dependency baked in
- No AI observability layer
- Technical debt from speed decisions
- Rebuilt when requirements evolve
Offshore dev shops
Cheap to start. Expensive to fix.
- AI expertise shallow or borrowed
- Prompt engineering done ad-hoc
- No production monitoring built in
- Architecture decisions cut for cost
- No long-term support ownership
- Code handoff without documentation
Acsenix
Shipped in weeks. Built to last. Yours forever.
- 6–12 weeks to production
- Model-agnostic architecture from day one
- Full-stack: front-end, back-end, AI layer
- Production observability built in
- Ongoing AMC — product improves post-launch
- 100% code & IP ownership
Questions we hear on every discovery call.
Straightforward answers — no sales spin.
Ask us directlyStop waiting 12 months
for AI your users actually see.
Book a discovery call. We'll scope your AI application, define the architecture, and show you exactly what we can ship in 6–12 weeks.
Free architecture scoping included. No commitment required.