44% → 98%
Clinical triage — Schmitt-Thompson
Guideline-executing triage lifting a raw LLM from 44% to 98% on the open 50-scenario benchmark — a domain where a wrong answer is a patient-safety event.
Agentic AI
Agentic AI that reaches production, not just the pilot stage.
Vstorm builds autonomous agents for mid-market companies — scoped to real workflows, evaluated before launch, and handed over so your team owns what runs.
Trusted by teams in production
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+11.76% orders from day 1 of the Australian launchThree-agent product advisor guiding customers through print-order configuration.
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2 hrs → 3 min to generate a workflowText-to-workflow agents building validated node graphs inside the platform.
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44% → 98% raw LLM vs guideline-executing accuracy on the open 50-scenario benchmarkHIPAA-compliant guideline-executing triage — 44% to 98% on the open 50-scenario benchmark.
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Supply chain intelligence agents reducing manual coordination overhead.
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37 kernels ported from CUDA to Intel GaudiProduction AI workloads moved to new hardware for on-prem LLM deployment.
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6 agents orchestrated by one supervisorMulti-agent financial coach: pattern extraction, gamified habit-building and two coaching personas with opposite attitudes.
What agentic AI is
Agency is the difference: planning and acting, not answering
Agentic AI gives a system genuine agency — it sets priorities, plans multi-step work, calls the tools it needs and adapts when the input changes, rather than responding to one prompt at a time. That is what turns AI from a demo into operating capability, and it is also why evaluation and guardrails matter more than model choice.
Every figure here is a published client outcome tied to the evaluation set it was measured against — the standard we suggest you hold any vendor to.
95.4%
Workflow success rate — Mixam
The client aimed for 80% accuracy to be usable. The delivered multi-agent product advisor exceeded it in production, with an 11.76% order increase on day one of the Australian launch.
2 hrs → 3 min
Workflow generation — Synera
Engineers moved from hours of tedious setup to minutes, through multi-step validation rather than a single generation pass.
What you get
What we deliver
From use-case selection to production agents your team can operate.
01
Use cases ranked by ROI
We start from your workflows, not from a technology menu — mapping where an agent moves the needle and what it is worth before anything is built.
02
Proof of Value on real data
A working prototype tested against your live scenarios, with a clear verdict on technical viability and projected ROI before you commit an engineering budget.
03
Sovereign and on-premise capable
Model-agnostic architecture on open-source foundations. Where required, agents run entirely inside your environment — no external API calls, no data leaving your domain.
04
Ownership transfer, not dependency
Code, architecture, evaluation suites and runbooks are handed over with training, so your team can operate and extend the system without us.
How we work
TriStorm — from business goal to production agent
Strategy, Proof of Value and engineering in one path, delivered by one team — with a go/no-go gate before any large-scale commitment.
Strategic alignment and planning
A workshop-driven stage that turns AI goals into a measurable rollout plan. We rank use cases by value, feasibility and risk, and document today's workflows alongside the target operating model.
- Ranked use cases
- Agent architecture and stack
- Human-in-the-loop checkpoints
Proof of Value
A working prototype on your real data and edge cases, with an evaluation suite and guardrails. It ends at a go/no-go gate — you decide on evidence, before any large-scale build.
- Working prototype on real data
- Evaluation suite and guardrails
- Go/no-go decision
Process augmentation
Production rollout with monitoring, alerting and ownership transfer. The team that wrote the business case is still in the room when the system goes live.
- Production deployment
- Monitoring and runbooks
- Team training and handover
Proof in practice
Agents running in production, with the numbers behind them
Published outcomes, each linked to the full case study.
“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.”
95.4%
Success rate in workflow results
Schmitt-Thompson · Clinical triage
Nurse-triage guidance where a wrong recommendation is a patient-safety event — staged retrieval and validation rather than one model answering in a single pass.
44% → 98%
raw LLM vs guideline-executing accuracy on the open 50-scenario benchmark
Why Vstorm
Credentials you can verify
Not adjectives — memberships, partnerships and open-source work anyone can check.
01
Agentic AI Foundation
First tech consultancy accepted as a member — contributing to the standards for how production agents get built.
02
Official Pydantic partner
Official Pydantic implementation partner, working with the framework since its beta versions.
03
Open source in production
Our agentic AI libraries are used by developers worldwide; we contribute to the tooling we deliver on, rather than only consuming it.
FAQ
Agentic AI, answered
What is agentic AI and how does it differ from traditional AI solutions?
Agentic AI represents autonomous systems that independently plan, execute, and adapt to achieve specific business goals without constant human oversight. Unlike traditional AI that responds to prompts, our agentic AI solutions proactively identify opportunities, make decisions, and take action. These intelligent ai agents continuously learn from outcomes, making them ideal for dynamic business environments.
How can Agentic AI work within our existing business systems and workflows?
Our Agentic AI systems integrate seamlessly with your current infrastructure through APIs and existing software platforms. These AI Agents operate within established workflows while enhancing efficiency and decision-making capabilities. Vstorm's implementation approach ensures agentic automation complements rather than replaces your team's expertise.
What are the proven use cases where Agentic AI delivers measurable ROI?
Proven agentic AI use cases include customer service automation, supply chain optimization, financial analysis, and marketing personalization. Our clients see 40-60% efficiency gains in these ai applications. Common agentic AI uses span lead qualification, inventory management, and predictive maintenance.
How do we implement Agentic AI without disrupting our current operations?
Vstorm follows a phased Agentic AI adoption strategy that minimizes operational disruption. We begin with pilot programs in non-critical areas, allowing your team to familiarize themselves with agentic AI tools gradually. Our implementation methodology ensures smooth integration of agentic ai applications while maintaining business continuity.
What advantages does Agentic AI offer over our current automation tools?
The advantages of Agentic AI include autonomous decision-making, adaptive learning, and goal-oriented behavior that surpasses traditional automation. While conventional AI tools require explicit programming for each scenario, our agentic ai system independently navigates complex situations and unexpected challenges. Vstorm's Agentic AI vs traditional approaches comparison shows 3x improvement in handling edge cases.
Which industries benefit most from Agentic AI applications?
Healthcare, financial services, manufacturing, and e-commerce see exceptional results from Agentic AI in action. These sectors leverage our AI applications for patient care optimization, fraud detection, predictive maintenance, and personalized customer experiences. Vstorm's agentic AI tools adapt to industry-specific requirements and compliance needs.
How long does Agentic AI adoption typically take for mid-sized businesses?
Typical Agentic AI adoption timelines range from 3-6 months for mid-sized organizations, depending on complexity and integration requirements. Vstorm's structured implementation process includes discovery, pilot deployment, testing, and full rollout phases. Most clients see initial benefits within 30-45 days of deployment.
What's the difference between Agentic AI and generative AI for business use?
Generative AI creates content and responses, while agentic AI and generative AI work together to create autonomous business solutions. Agentic AI uses generative capabilities for communication but focuses primarily on independent action and decision-making. Vstorm combines both technologies in our comprehensive ai solutions, enabling systems that can both generate insights and act upon them autonomously.
Do we need technical expertise in-house to use Agentic AI solutions?
Vstorm's Agentic AI solutions are designed for business users, not just technical teams. Our intuitive interfaces and comprehensive training programs enable non-technical staff to effectively manage and optimize AI Agents. While technical support enhances implementation, it's not required for day-to-day operations. We provide ongoing support and maintenance for complex ai system components.
How do we measure success when implementing Agentic AI systems?
Success metrics for Agentic AI implementation include efficiency gains, cost reduction, accuracy improvements, and customer satisfaction scores. Vstorm provides comprehensive analytics dashboards that track ai agent performance, decision quality, and business impact. Key performance indicators vary by AI use case but typically show 25-50% improvement in targeted processes.
Work with us
Ready to see what an agent would do in your workflow?
Book a 45-minute consultation. We map one real process worth automating and what proving it would take.
