Vstorm vs Deviniti: full comparison for 2026
Last updated: August 2026
Quick verdict
Vstorm (4.4/5) edges ahead of Deviniti (3.8/5) overall. Vstorm is the better choice for buyers wanting a genuinely small agency whose entire practice is agentic AI, with an independently verifiable AAIF credential.. Deviniti is the stronger option for buyers on the Atlassian ecosystem wanting an agency with an independently checkable marketplace/partner track record.. The right choice depends on your project size, budget, and required tech stack.
Vstorm vs Deviniti: head-to-head summary
| Criterion | Vstorm | Deviniti |
|---|---|---|
| Founded | 2017 | 2004 |
| HQ | Wrocław, Poland | Wrocław, Poland |
| Team size | 11–50 | 201–500 |
| Rating | 4.4 / 5 | 3.8 / 5 |
| Best for | Buyers wanting a genuinely small agency whose entire practice is agentic AI, with an independently verifiable AAIF credential. | Buyers on the Atlassian ecosystem wanting an agency with an independently checkable marketplace/partner track record. |
| Pricing model | Fixed project, dedicated team | Fixed project, dedicated team |
| Min. engagement | Not published | $20K (per company website; independently unverifiable) |
| Primary tech stack | Python, LangChain, LangGraph | Python, Java, LangChain |
| Industries served | Technology & SaaS, Financial Services, Retail & E-commerce | Financial Services, Manufacturing, Technology & SaaS, Retail & E-commerce |
Vstorm vs Deviniti: overview
Vstorm
Vstorm is a Wrocław, Poland-based boutique agency founded in October 2017 by CEO Antoni Kozelski and VP Bartosz Gonczarek, with a compact team of 11–50 people, operating exclusively as an agentic AI engineering consultancy. It was the first AI consultancy accepted into the Agentic AI Foundation (AAIF) and publishes its own TriStorm delivery framework. As an 11–50 person shop, it sits at the smaller end of this list, giving buyers direct access to the same senior engineers who scope the work.
Deviniti
Deviniti is a Wrocław, Poland-based software agency founded in 2004 by Piotr Dorosz and Jacek Machata, with roughly 260 employees across Europe and North America. Its established Atlassian Marketplace app and consulting business gives buyers a checkable, independently reviewable track record beyond the agency's self-reported claims — a useful reference point most competitors on this list lack.
Services and capabilities: Vstorm vs Deviniti
| Capability | Vstorm | Deviniti |
|---|---|---|
| Multi-agent orchestration | ✓ | ✗ |
| RAG / knowledge integration | ✓ | ✗ |
| Workflow & systems integration | ✗ | ✓ |
| Coding agents | ✗ | ✗ |
| Monitoring & anomaly detection | ✗ | ✗ |
| Customer-facing agents | ✗ | ✗ |
Tech stack comparison: Vstorm vs Deviniti
| Framework / platform | Vstorm | Deviniti |
|---|---|---|
| LangChain | ✓ | ✓ |
| LangGraph | ✓ | N/A |
| AutoGen | N/A | N/A |
| LlamaIndex | N/A | N/A |
| OpenAI | ✓ | N/A |
| Anthropic Claude | ✓ | N/A |
| Pinecone | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Vstorm vs Deviniti
| Criterion | Vstorm | Deviniti |
|---|---|---|
| Minimum engagement | Not published | $20K (per company website; independently unverifiable) |
| Engagement models | Fixed project, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Mid-market | Accessible |
Target audience comparison: Vstorm vs Deviniti
| Dimension | Vstorm | Deviniti |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Technology & SaaS, Financial Services, Retail & E-commerce | Financial Services, Manufacturing, Technology & SaaS |
| Best use cases | Buyers wanting a vendor whose entire business is agentic AI, at a small-agency scale, Teams wanting standardized AGENTS.md documentation baked into delivery | Buyers wanting an agency whose track record can be independently checked via a third-party marketplace, Workflow-integration agents for teams already running Atlassian tooling |
| Typical project type | Fixed project | Fixed project |
Vstorm vs Deviniti: pros and cons
| Vstorm | |
|---|---|
| + | First AI consultancy formally accepted into the Agentic AI Foundation, an independently verifiable credential |
| + | Genuinely boutique scale (11–50 people) means direct access to the engineers who scope the work |
| + | Named proprietary delivery framework (TriStorm) gives buyers a concrete methodology to evaluate |
| + | Public commitment to AGENTS.md documentation on every project, easing long-term maintainability |
| - | 11–50 person team caps capacity for large or highly parallel programs |
| - | Founded relatively recently (October 2017) relative to some longer-tenured agencies on this list |
| - | Minimum engagement figures are not published, requiring direct sales contact for early budgeting |
| Deviniti | |
|---|---|
| + | Atlassian Marketplace and partner listings give buyers an independently checkable track record |
| + | Two decades of enterprise systems-integration experience, originally rooted in financial-sector IT |
| + | ~260-person team spread across Europe and North America for regional delivery coverage |
| + | Founder-led continuity since 2004 provides institutional stability |
| - | Agentic AI is a newer addition to a legacy enterprise-software and Atlassian practice |
| - | Less name recognition in AI-specific procurement circles compared to AI-first competitors |
| - | Public agentic-specific case studies are limited relative to its Atlassian portfolio |
Who should choose Vstorm?
Vstorm is the right choice for buyers wanting a genuinely small agency whose entire practice is agentic AI, with an independently verifiable AAIF credential..
First AI consultancy accepted into the Agentic AI Foundation, at a genuinely boutique (11–50 person) agency scale.. Minimum engagement starts at Not published. Works best with clients in Technology & SaaS, Financial Services, Retail & E-commerce.
Who should choose Deviniti?
Deviniti is the right choice for buyers on the Atlassian ecosystem wanting an agency with an independently checkable marketplace/partner track record..
An Atlassian Marketplace and partner track record independently checkable outside the agency's own claims, applied to agent workflow integration.. Minimum engagement starts at $20K (per company website; independently unverifiable). Works best with clients in Financial Services, Manufacturing, Technology & SaaS, Retail & E-commerce.
Decision matrix: Vstorm vs Deviniti
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Vstorm |
| You need a large dedicated team for an ongoing programme | Vstorm |
| Your budget is at the lower end | Compare: Vstorm (Not published) vs Deviniti ($20K (per company website; independently unverifiable)) |
| You need specialist depth in a specific vertical | Deviniti |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: Vstorm vs Deviniti
| Use case | Vstorm fit | Deviniti fit | Winner |
|---|---|---|---|
| Buyers wanting a vendor whose entire business is agentic AI, at a small-agency scale | Strong | Strong | Both equally |
| Teams wanting standardized AGENTS.md documentation baked into delivery | Strong | Strong | Both equally |
| Buyers wanting an agency whose track record can be independently checked via a third-party marketplace | Strong | Strong | Both equally |
| Workflow-integration agents for teams already running Atlassian tooling | Limited | Strong | Deviniti |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Vstorm vs Deviniti
Vstorm (4.4/5) is the stronger overall choice for most AI Agent Development projects. First AI consultancy accepted into the Agentic AI Foundation, at a genuinely boutique (11–50 person) agency scale.. It is best for buyers wanting a genuinely small agency whose entire practice is agentic AI, with an independently verifiable AAIF credential..
Deviniti (3.8/5) is the better choice when buyers on the Atlassian ecosystem wanting an agency with an independently checkable marketplace/partner track record.. If your situation matches those criteria, Deviniti is a competitive option.
Related comparisons
Vstorm vs Deviniti FAQ
Is Vstorm better than Deviniti?
Vstorm (4.4/5) scores higher overall, but "better" depends on your use case. Vstorm is better for buyers wanting a genuinely small agency whose entire practice is agentic AI, with an independently verifiable AAIF credential.. Deviniti is better for buyers on the Atlassian ecosystem wanting an agency with an independently checkable marketplace/partner track record..
How do Vstorm and Deviniti differ in pricing?
Vstorm uses fixed project, dedicated team pricing with a minimum engagement of Not published. Deviniti uses fixed project, dedicated team pricing with a minimum engagement of $20K (per company website; independently unverifiable). Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Vstorm or Deviniti?
Deviniti is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Vstorm and Deviniti?
Vstorm's primary differentiator is: first ai consultancy accepted into the agentic ai foundation, at a genuinely boutique (11–50 person) agency scale.. Deviniti's primary differentiator is: an atlassian marketplace and partner track record independently checkable outside the agency's own claims, applied to agent workflow integration.. They also differ in team size (11–50 vs 201–500), minimum engagement (Not published vs $20K (per company website; independently unverifiable)), and primary industries served (Technology & SaaS, Financial Services vs Financial Services, Manufacturing).
Last reviewed: August 2026. Verify all details directly with each agency before making a decision.