We build AI agents
that run in production.
Vstorm is an applied agentic AI engineering consultancy for mid-market challengers. Through the TriStorm methodology, we take one real workflow from strategy to a production system your team owns.
You're chatting with an AI versed in our content. How we handle this chat
Trusted across 30+ production deployments. Inspired by our customers.
“My wish was at least an 80% success rate — we finished over 95.4%, so it exceeded expectations.”
Mapline.AI 
“Very professional at every step — their insight helped us greatly and made the process feel seamless.”
Mapline.AI 
“My wish was at least an 80% success rate — we finished over 95.4%, so it exceeded expectations.”
Mapline.AI “Very professional at every step — their insight helped us greatly and made the process feel seamless.”
Mapline.AI Each stall has a different cause and a different first move. Pick the description that sounds like your organisation.
There is a strategy, a vendor shortlist, and possibly a pilot that impressed the board. Between that plan and a working system sits engineering nobody in the building owns.
How a workflow reaches productionRPA, Zapier, or an off-the-shelf platform covered the simple half. The cross-department workflows that actually cost money were too specific, too multi-step, too dependent on tribal knowledge.
How we engineer the hard halfYour team knows models. Orchestrating agents in production, keeping them reliable, and wiring them into your existing systems is a different skill set — slow to build from scratch without help.
How we accelerate an existing teamBoth are first steps, not proposals. One is self-guided and lands in your inbox; the other is 45 minutes with the engineers who would do the work.
A guided assessment that profiles your organisation across seven dimensions and names the gaps most likely to block production. The profile is yours to use internally, whether or not you continue with Vstorm.
A focused session with people who have shipped production agentic AI. We take one of your workflows, map it to an agentic design, and show systems already running in production.
Two entry packages for teams that already own part of the work, and one end-to-end programme when the whole agentic layer has to be built. Every engagement ends with your team owning what runs.
We show you the path and walk it with you. Your team builds the muscle.
You know what to build. We build it, inside your environment.
Zero to an operating agentic AI layer — strategy through engineering, end to end.
Inside the packages
After 30+ agent deployments — mid-market companies through enterprises like Mercedes — the same failure modes keep showing up. TriStorm is how we work through them in three phases.
We align on one workflow, prove value on a real case, then wire agents into the processes they need to run in day to day.
Explore TriStormNo stock photography. Every face here works at Vstorm, and the rooms are our office in Wrocław.
Engineers moved from hours of tedious setup to minutes, through multi-step validation rather than a single generation pass.
Read case study
A three-agent product advisor guiding customers through print-order configuration — 15 tools working against more than a billion product combinations.
Read case study Guideline-executing medical triage: the LLM answers triage assessment questions; disposition follows the guideline deterministically — 98% on the open 50-scenario benchmark, on par with a 94.4% nurse-panel correct-disposition rate.
Read case study
A bilingual English/Arabic autonomous agent embedded in ARIJ's Moodle environment, answering only from ARIJ's own knowledge base — across 22 countries.
Read case study
Three numbers we publish everywhere, and what each one actually counts. The open-source figures sit in the band above, with the date they were counted.
Retrieve, verify, call tools, and route edge cases to a human when policy requires it. Every step goes in the audit log.
Illustrative walkthrough of a claims-triage agent — the log and these figures are scripted, not telemetry from a client system. The measured numbers are in the case studies above.
Behind the libraries: the same engineers as the 30+ production deployments.
The first
Agentic AI Consultancy
joined the
to contribute
and help set
where the field goes.
Official partners on the frameworks
we ship in production
Four engineering practices for teams moving language models from pilot to production: strategy, retrieval, agent frameworks, and operations.
Full services catalogRAG pipelines built for your data and your workflows — retrieval, grounding, and evaluation so answers in production stay tied to source material.
ExploreWe work out which workflows LLMs can actually improve, what to build first, and what to skip.
Explore Official Pydantic implementation partner. We build typed, testable agents on Pydantic AI that your team can run and extend after handover.
ExploreFor LLMs already live: monitoring, evals, version rollouts, cost tracking, and regression checks as traffic and models change.
Explore
“My wish was to come to at least an 80% success rate in the workflow results, and by the time we finished the project, the success rate is, I believe, over 95.4% — so it definitely exceeded expectations.”
“Beyond saving engineering teams hundreds of valuable hours each quarter, Synera aims for the easiest to use AI agent platform to make the AI transformation for engineers as smooth and frictionless as possible.”
“The team at Vstorm was very helpful, their insight and experience helped us greatly in our project. They were very professional at every step of the way and made the whole process feel seamless.”
Most teams hit the hard part after the board signs off on the vision. We work with executives and operations leads on the path from strategy to a working system: where to start, how to structure a Proof of Value or MVP so it can scale, and what to change when priorities shift.
If RPA, Zapier, or a platform handled the simple cases but cross-department work still runs on tribal knowledge, we join what you already have. We review the architecture, integrate with your stack, embed alongside your team, and leave documentation your people can run without us.
When the bench knows models but production orchestration is the bottleneck, we add senior engineers on agent design, reliability, and integration. We advise on architecture, pair on the hard tickets, and make sure capability stays with you when we step back.
Book 45 minutes with our founders and senior AI engineers. We'll walk through what we've shipped across 30+ production deployments and name a realistic first step for your organisation — including cases where the answer is not to build yet.
