Vstorm vs Addepto: full comparison for 2026
Quick verdict
Vstorm (4.2/5) edges ahead of Addepto (4.0/5) overall. Vstorm is the better choice for teams whose LLM agent prototype needs engineers who have shipped agents before. Addepto is the stronger option for industrial and automotive companies that need data engineers who know factory data. The right choice depends on your project size, budget, and required tech stack.
Vstorm vs Addepto: head-to-head summary
| Criterion | Vstorm | Addepto |
|---|---|---|
| Founded | 2017 | 2017 |
| HQ | Wrocław, Poland | Warsaw, Poland |
| Team size | 10–49 | 50–249 |
| Rating | 4.2 / 5 | 4.0 / 5 |
| Primary differentiator | A team that works almost entirely on LLM agents and RAG | Data and ML engineers with industrial and automotive client history |
| Pricing model | $100–$149/hr (Clutch band); team extension or project billing | Monthly per engineer or project fee; rates on request |
| Min. engagement | $10,000+ | Not published |
| Primary tech stack | Python, LangChain, LlamaIndex | Python, Databricks, Spark |
| Industries served | SaaS, Legal, Financial services, Healthcare, Retail | Manufacturing, Automotive, Aviation, Retail, Logistics |
Vstorm vs Addepto: overview
Vstorm
Vstorm has been in business in Wrocław since 2017 and now builds almost nothing but LLM and agent software, including retrieval-augmented generation systems. Clutch shows an overall score of 4.9 from verified reviews, an hourly band of $100 to $149 and a $10,000 minimum project. The team is small, between 10 and 49 people on Clutch, so the engineers it lends out are the same people who build its own agent projects. That makes it a good source of agent expertise but a poor one for headcount.
Addepto
Addepto was founded in Warsaw in 2017 and works on AI, ML and data engineering, mostly for industrial and automotive clients. KMS Technology acquired it in December 2025, so it now sits inside a larger U.S.-based IT group. Addepto supplies data and ML engineers for team extension as well as running projects. The acquisition may widen its bench over time, but buyers should expect changes to contracts and account management as the integration proceeds.
Services and capabilities: Vstorm vs Addepto
| Capability | Vstorm | Addepto |
|---|---|---|
| ML engineers | ✗ | ✓ |
| LLM / GenAI engineers | ✓ | ✓ |
| AI agent developers | ✓ | ✗ |
| MLOps engineers | ✗ | ✗ |
| Computer vision engineers | ✗ | ✗ |
| NLP engineers | ✗ | ✗ |
| Data engineers | ✗ | ✓ |
| Engineer-led technical screen | ✓ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
| Direct hire option | ✗ | ✗ |
Tech stack comparison: Vstorm vs Addepto
| Framework / platform | Vstorm | Addepto |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Vstorm vs Addepto
| Criterion | Vstorm | Addepto |
|---|---|---|
| Minimum engagement | $10,000+ | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Dedicated engineer, Dedicated team, Project delivery |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Vstorm vs Addepto
| Dimension | Vstorm | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Legal, Financial services | Manufacturing, Automotive, Aviation |
| Best use cases | Rescuing an agent that fails on multi-step tool calls, Adding a RAG engineer to improve retrieval quality | Adding a data engineer to an automotive analytics platform, Building a predictive maintenance model with a two-person team |
| Typical project type | Dedicated engineer | Dedicated engineer |
Vstorm vs Addepto: pros and cons
| Vstorm | |
|---|---|
| + | Verified Clutch score of 4.9 with a published rate band |
| + | Narrow focus on agents and RAG means deep, current experience |
| + | Engineers come from its own build team, not a recruiting pool |
| - | Small team, so only one or two engineers at a time |
| - | Higher hourly band than most Central European suppliers |
| - | Little classic ML, computer vision or data engineering |
| Addepto | |
|---|---|
| + | Strong data engineering on Databricks and Azure |
| + | Industrial and automotive references |
| + | Backing from a larger group may add capacity |
| - | Acquired by KMS Technology in December 2025, so terms and contacts may change |
| - | Fewer computer-vision and NLP specialists than AI-research firms |
| - | Staffing evidence is thinner than its project work |
Who should choose Vstorm?
A typical fit: rescuing an agent that fails on multi-step tool calls.
A team that works almost entirely on LLM agents and RAG. Minimum engagement starts at $10,000+. Works best with clients in SaaS, Legal, Financial services, Healthcare, Retail.
Who should choose Addepto?
A typical fit: adding a data engineer to an automotive analytics platform.
Data and ML engineers with industrial and automotive client history. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Automotive, Aviation, Retail, Logistics.
Decision matrix: Vstorm vs Addepto
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Vstorm |
| You need one specialist for a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Addepto |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| Your budget is at the lower end | Compare: Vstorm ($10,000+) vs Addepto (Not published) |
| Your team works U.S. hours | Neither lists Latin American engineers; confirm overlap hours in the contract |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
Use case fit: Vstorm vs Addepto
| Use case | Vstorm fit | Addepto fit | Winner |
|---|---|---|---|
| Rescuing an agent that fails on multi-step tool calls | Strong | Limited | Vstorm |
| Adding a RAG engineer to improve retrieval quality | Strong | Strong | Both equally |
| Adding a data engineer to an automotive analytics platform | Strong | Strong | Both equally |
| Building a predictive maintenance model with a two-person team | Strong | Strong | Both equally |
Verdict: Vstorm vs Addepto
Vstorm (4.2/5) is the stronger overall choice for most AI Engineer Staffing projects. A team that works almost entirely on LLM agents and RAG.
Addepto (4.0/5) is worth a look if you need building a predictive maintenance model with a two-person team. If your situation matches that, Addepto is a competitive option.
Related comparisons
Vstorm vs Addepto FAQ
Is Vstorm better than Addepto?
Vstorm (4.2/5) scores higher overall, but "better" depends on your use case. Vstorm's strongest advantage: verified Clutch score of 4.9 with a published rate band. Addepto's strongest advantage: strong data engineering on Databricks and Azure.
How do Vstorm and Addepto differ in pricing?
Vstorm uses $100–$149/hr (clutch band); team extension or project billing pricing with a minimum engagement of $10,000+. Addepto uses monthly per engineer or project fee; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Vstorm or Addepto?
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 Vstorm and Addepto?
Vstorm's primary differentiator is: a team that works almost entirely on LLM agents and RAG. Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. They also differ in team size (10–49 vs 50–249), minimum engagement ($10,000+ vs Not published), and primary industries served (SaaS, Legal vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.