Addepto vs Vstorm: full comparison for 2026
Quick verdict
Addepto (4.3/5) edges ahead of Vstorm (4.3/5) overall. Addepto is the better choice for data teams needing warehouse work before an LLM project. Vstorm is the stronger option for teams wanting agents they will own and maintain. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Vstorm: head-to-head summary
| Criterion | Addepto | Vstorm |
|---|---|---|
| Founded | 2018 | 2017 |
| HQ | Warsaw, Poland | Wrocław, Poland |
| Team size | 50–249 | 10–49 |
| Rating | 4.3 / 5 | 4.3 / 5 |
| Primary differentiator | Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored | Agent specialists who hand over a production system the client team can maintain without them |
| Pricing model | $50–$99/hr (Clutch band); discovery workshops, then T&M | Fixed-scope workshops and builds, then T&M; rates on request |
| Min. engagement | $10,000+ (Clutch) | Not disclosed |
| Primary tech stack | Databricks, Snowflake, Azure OpenAI | PydanticAI, LangChain, LangGraph |
| Industries served | Manufacturing, Retail & e-commerce, Aviation, Financial services | Manufacturing, Financial services, Professional services |
Addepto vs Vstorm: overview
Addepto
Addepto is a Warsaw-based AI and data consultancy that started trading in April 2018 (some directories list 2017). Clutch shows 50–249 employees, a $50–$99 hourly band and a $10,000 minimum project. CB Insights reports that KMS Technology acquired the company in December 2025, after an earlier tie-up with Grape Up. Its work typically begins with data engineering and moves on to generative AI, MLOps and AI discovery workshops.
Vstorm
Vstorm is a small agentic-AI consultancy founded in 2017 in Wrocław, Poland, with 10–49 employees according to Clutch. It focuses on retrieval-augmented generation and multi-step agents for business processes, and says it was the first partner of PydanticAI and the first consulting firm to join the Agentic AI Foundation (per company website; independently unverifiable). Its TriStorm method takes a workflow from strategy through a production agent that the client's own team owns afterwards.
Services and capabilities: Addepto vs Vstorm
| Capability | Addepto | Vstorm |
|---|---|---|
| CRM / ERP integration | ✗ | ✗ |
| LLM API gateway & cost control | ✓ | ✓ |
| Document processing | ✗ | ✗ |
| Agentic workflows | ✗ | ✓ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✗ | ✗ |
| PII masking & access control | ✗ | ✗ |
Tech stack comparison: Addepto vs Vstorm
| Framework / platform | Addepto | Vstorm |
|---|---|---|
| Salesforce | N/A | N/A |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | N/A | N/A |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | N/A |
| Databricks | ✓ | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | N/A | N/A |
| LangChain | ✓ | ✓ |
| ServiceNow | N/A | N/A |
Pricing comparison: Addepto vs Vstorm
| Criterion | Addepto | Vstorm |
|---|---|---|
| Minimum engagement | $10,000+ (Clutch) | Not disclosed |
| Engagement models | Fixed project, Time & materials | Fixed project, Time & materials |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Addepto vs Vstorm
| Dimension | Addepto | Vstorm |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail & e-commerce, Aviation | Manufacturing, Financial services, Professional services |
| Best use cases | Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant., Productionizing ML models with MLflow and monitoring. | An internal agent that triages inbound requests and drafts responses for review., Retrieval over technical or contractual documents with citations. |
| Typical project type | Fixed project | Fixed project |
Addepto vs Vstorm: pros and cons
| Addepto | |
|---|---|
| + | Publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward |
| + | Databricks and Spark experience helps when the data estate is the real blocker |
| + | Discovery workshops scope use cases before larger spend |
| + | Predictive analytics and LLM work available from the same team |
| - | Acquired by KMS Technology in December 2025 (per CB Insights), so ownership and leadership may change |
| - | Corporate history includes several restructurings, which complicates long-term vendor planning |
| - | Limited published work inside CRM platforms |
| Vstorm | |
|---|---|
| + | Narrow focus on agents means the team has seen many of the failure modes before |
| + | Handover to the client team is designed in from the start |
| + | Early contributor to open agent frameworks such as PydanticAI |
| + | Small enough that senior engineers do the actual work |
| - | A team under 50 limits how many parallel workstreams it can run |
| - | Few published examples of deep ERP or CRM integration |
| - | Client and partnership claims come mostly from its own materials |
Who should choose Addepto?
A typical fit: building a Databricks lakehouse that later feeds demand forecasts and an internal assistant.
Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Manufacturing, Retail & e-commerce, Aviation, Financial services.
Who should choose Vstorm?
A typical fit: an internal agent that triages inbound requests and drafts responses for review.
Agent specialists who hand over a production system the client team can maintain without them. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Financial services, Professional services.
Decision matrix: Addepto vs Vstorm
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Neither advertises one; ask for a scoped pilot |
| AI has to work inside your existing CRM or ERP | Neither lists CRM/ERP integration work |
| Personal data must be masked and answers limited by user permissions | Ask both for their PII and access-control design |
| Your budget is at the lower end | Compare: Addepto ($10,000+ (Clutch)) vs Vstorm (Not disclosed) |
| You want the vendor to run the AI service after launch | Neither offers managed services; plan in-house operations |
| You are building multi-step agents across systems | Vstorm |
Use case fit: Addepto vs Vstorm
| Use case | Addepto fit | Vstorm fit | Winner |
|---|---|---|---|
| Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant. | Strong | Limited | Addepto |
| Productionizing ML models with MLflow and monitoring. | Strong | Limited | Addepto |
| An internal agent that triages inbound requests and drafts responses for review. | Strong | Strong | Both equally |
| Retrieval over technical or contractual documents with citations. | Limited | Strong | Vstorm |
Verdict: Addepto vs Vstorm
Addepto (4.3/5) is the stronger overall choice for most AI Integration projects. Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored.
Vstorm (4.3/5) is worth a look if you need retrieval over technical or contractual documents with citations. If your situation matches that, Vstorm is a competitive option.
Related comparisons
Addepto vs Vstorm FAQ
Is Addepto better than Vstorm?
Addepto (4.3/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward. Vstorm's strongest advantage: narrow focus on agents means the team has seen many of the failure modes before.
How do Addepto and Vstorm differ in pricing?
Addepto pricing: $50–$99/hr (Clutch band); discovery workshops, then T&M. Minimum engagement: $10,000+ (Clutch). Vstorm pricing: Fixed-scope workshops and builds, then T&M; rates on request. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or Vstorm?
Addepto is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between Addepto and Vstorm?
Addepto's primary differentiator is: data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. Vstorm's primary differentiator is: agent specialists who hand over a production system the client team can maintain without them. They also differ in team size (50–249 vs 10–49), minimum engagement ($10,000+ (Clutch) vs Not disclosed), and primary industries served (Manufacturing, Retail & e-commerce vs Manufacturing, Financial services).
Verify all details directly with each company before making a decision.