The full AI engineering
stack, under one roof.
From process discovery to full-stack AI product delivery — six interconnected capabilities, one accountable delivery partner, 100% code ownership from day one.
6
core service capabilities
2–12w
discovery to production
100%
source code ownership
$180k
avg waste found in discovery
Six capabilities. Every layer of your AI transformation.
AI Workflow Automation
End-to-end intelligent process automation — document ingestion, cross-system orchestration, approval routing — eliminating manual work at scale.
Custom AI Agents
Autonomous agents tuned to your domain — multi-step reasoning, tool use, and persistent memory built around your actual workflows.
Data Pipeline Automation
Real-time ingestion, transformation, and orchestration across your entire data stack — with zero manual intervention and full observability.
LLM Integration
Language model embedding across your existing stack — RAG pipelines, semantic search, structured output, prompt systems, and model-switching architecture.
AI App Development
Full-stack AI product engineering — agentic backends, real-time interfaces, and production-grade MLOps delivered in 6–12 weeks with 100% code ownership.
Process Intelligence
$180k avg waste foundMap your workflows, score every process against automation potential, and receive a build-ready roadmap with hard ROI numbers — before a single line of code is written.
What's included regardless of which service you start with.
Full source code ownership
You own everything — no licensing fees, no platform lock-in, no Acsenix dependency after handoff.
Working POC in 2–4 weeks
Every engagement starts with a proof-of-concept on real data before any long-term commitment.
Documented architecture
Every system is delivered with architecture diagrams, operational runbooks, and staff training.
Ongoing AMC available
Post-launch sprint cycles to iterate, improve, and expand — so your AI system grows with your business.
Not sure which service fits? Start here.
Most engagements begin with one capability and expand from there. Here are the three most common entry points.
Automate existing operations
If you have manual workflows eating time and budget, start with discovery and automation.
Build a new AI product
If you're shipping an AI-powered application or embedding AI into an existing product.
Scale data infrastructure
If your data pipelines can't support the AI systems you want to build.
How every Acsenix engagement runs.
Every service follows the same structured delivery model — so you always know where you are, what's next, and what you'll hold us to.
Start with a discovery callDiscovery
We map your current state — workflows, systems, data, and goals — and produce a precise technical scope before any build begins.
POC on Real Data
A working proof-of-concept on your actual data and systems in 2–4 weeks. Nothing theoretical.
Build & Iterate
Weekly sprint demos on real data. Integration testing throughout. You see progress every week.
Deploy & Hand Off
Production deployment with monitoring, runbooks, and full source code transfer. Everything documented.
Ready to build?
Tell us what you're trying to solve.
Book a discovery call. We'll identify the right capability for your situation and show you exactly what a first engagement looks like — before any commitment.
Free architecture scoping on your first call. No commitment required.