AI that works in the demo.
AI that works in production.
AI that works on Monday morning.
Most AI projects impress in the pitch and fail in the pipeline. We build AI systems your team can actually rely on: knowledge assistants, workflow automation, and agent operations that are observable, cost-efficient, and engineered for real business use.
UI & Chat
A polished, streaming chat surface — not a raw API.
Production, not demos
Systems running in real client environments — engineered for real business use.
Self-hosted
Deployed into your cloud. Your data and models never leave your environment.
Observable by default
Every agent monitored, cost-controlled, and governed from day one.
Engineered to last
Tested, instrumented, documented — built for your team to own and extend.
Companies that trust us
- Nodewave
- Flowmint
- Quanta
- Hivebase
- Brightloop
The problem we solve
AI is easy to prototype. Hard to operate.
The gap between a convincing demo and a system you can run a business on is enormous — and it's exactly where most teams get stuck. These are the six failures we're built to close.
AI responses aren't reliable.
It's confident, then wrong — and there's no guarantee the next answer holds up on real data.
Costs keep climbing.
Token spend creeps up with no budget, no per-run visibility, and no alert before the bill arrives.
Knowledge is scattered.
The answers live across docs, tickets, and tools, so the model can't ground itself in what you actually know.
Teams still do repetitive work.
The busywork you hoped to automate is still done by hand, because the AI never made it into the workflow.
No visibility into AI performance.
When something drifts or breaks, there are no traces, no evals, and no alert — so nobody trusts it.
It works in demos, not production.
A slick proof-of-concept gets signed off, then falls over on real load and the edge cases nobody scripted.
What we build
Outcomes, not integrations.
AI Agent Engineering
Custom AI agents built around your real workflows — with deterministic execution you can trust in production.
Knowledge Systems
An internal ChatGPT over your own data: RAG, document intelligence, and enterprise search that stays grounded.
AI Operations
Monitoring, cost optimization, governance, and deterministic execution — so your AI keeps working after launch.
Why Stacx24
You don't get an API call. You get a runtime.
Most agencies stop at the model. We deploy the Stacx24 Runtime into your environment — a control plane that makes every agent observable, cost-controlled, and governed.
Self-hosted: your data and models never leave your cloud.
Stacx24 Runtime
Self-hosted in your environment
How we work
Discovery to optimization, one clear path.
Discovery
We map the workflow, the data, and the failure modes — and agree what 'working' means.
AI Strategy
We choose the models, retrieval, and guardrails, and scope a first version worth shipping.
Build
Engineered like software — tested, evaluated, and observable, not vibes.
Deploy
Shipped into your environment on the Stacx24 Runtime, with rollback.
Operate
Monitored, cost-controlled, and governed — with alerts when something drifts.
Optimize
We tune on real usage and hand it over documented, so your team can extend it.
Case study
One system, shipped to production.
How a PR agency scaled SEO and content with 30+ AI agents
- Problem
- A mid-size PR agency's edge was research-backed content and technical SEO — but that quality was manual, and manual couldn't scale with client demand.
- Solution
- We built a fleet of 30+ production agents (Claude + OpenAI) on the Stacx24 Runtime — technical SEO, PR research, content, three directory sites, and competitor analysis — with people approving, not assembling.
- Result
- 1,000+ research-backed articles, three niche directory sites, and always-on SEO — every agent observable and cost-controlled.
Testimonials
What our clients say.
“StacX24 shipped our RAG assistant in five weeks and it actually held up in production — grounded answers, real citations, no hallucinated nonsense. The first thing our team has fully trusted.”
“They cut our weekly reporting from two days to a few minutes with an agent that just works. Communication was sharp and they sweated the edge cases we hadn't even thought of.”
“We needed a directory that ranks itself and scales. StacX24 delivered a full-stack product that's fast, clean, and climbing search. Felt like a senior team, not a vendor.”
Industries
Where we've shipped.
- Software
- Digital Agencies
- Agriculture
- Textile
- Real Estate
Why clients choose us
What you get with Stacx24.
Production-first AI
We build for real load and edge cases, not the demo.
AI engineering
Evals, tests, and observability — engineered, not prompted.
Cost control
Every run measured and budgeted, so spend never surprises you.
Fast delivery
A shippable first version in weeks, not quarters.
Secure architecture
Self-hosted in your cloud; your data stays yours.
Long-term partnership
We hand over documented systems and stay for what's next.
FAQ
The questions teams ask before they pick up the phone.
- How long does an AI project take?
- Weeks, not quarters. A sharply-scoped first version is usually live in 4–8 weeks; smaller pilots can ship in two. We size scope to what can be shipped — and measured — inside that window, then expand.
- Which LLMs do you support?
- All the major ones — Claude, OpenAI, and Gemini — plus open-source models where they fit. The Stacx24 Runtime sits in front of the model, so you can switch providers without rebuilding your product.
- Can you integrate with our existing systems?
- Yes. We connect agents to the tools and data you already run — CRMs, databases, internal APIs, document stores — and default to your existing stack wherever it fits.
- Do you offer ongoing support?
- Yes. We monitor, tune, and govern what we ship, and hand it over documented so your team can run and extend it. We stay on for the next iteration when you want us to.
- Can we run it in our own cloud?
- Always. The Stacx24 Runtime is self-hosted — it deploys into your environment, so your data and models never leave your cloud. Observability, cost control, and governance run entirely on your infrastructure.
Tell us the workflow you'd kill first.
Bring the messiest, most manual part of your operation. We'll tell you — straight — whether AI should touch it, and how we'd ship it.