Vstorm vs Addepto: full comparison for 2026
Quick verdict
Vstorm (4.0/5) edges ahead of Addepto (3.9/5) overall. Vstorm is the better choice for teams whose agent prototype works in a demo but fails in production. Addepto is the stronger option for industrial and automotive companies adding AI and data engineers to an internal team. 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 | 40+ (25+ AI engineers per company) | 50–99 (directory estimate) |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Primary differentiator | Senior agent engineers who join an existing team to fix reliability and integration | AI-heavy team with manufacturing domain experience, now backed by a larger group |
| Pricing model | Monthly agentic-engineering retainer or 3+ month embedded package; $100–$149/hr (Clutch band) | Collaborative team model or managed delivery; rates on request |
| Min. engagement | $10,000+ (Clutch) | Not published |
| Primary tech stack | Python, PydanticAI, LangChain | Python, Databricks, Spark |
| Industries served | Fintech & payments, SaaS, Professional services | Manufacturing, Automotive, Retail, Aviation |
Vstorm vs Addepto: overview
Vstorm
Vstorm has built AI systems since 2017 and now concentrates on LLM agents, with about 25 AI engineers on its bench and 40+ staff in total, mostly in Wrocław and remote across Poland. Its website names three situations it fixes, and one is an existing team that has stalled; there, Vstorm adds senior engineers who specialize in agent design, reliability and integration. Its longest package embeds a manager, a tech lead and engineers for three months or more. Deloitte and EY have both recognized the company, according to directory listings.
Addepto
Addepto has worked on AI and data in Warsaw since 2017, with a strong client base in industrial and automotive companies. KMS Technology, an Atlanta engineering firm backed by Sunstone Partners, acquired it in December 2025. Its collaborative cooperation model puts Addepto engineers alongside the client's own team, and the company has said publicly it is not a body-leasing firm. After the deal, its CEO said 97% of the team are AI engineers.
Services and capabilities: Vstorm vs Addepto
| Capability | Vstorm | Addepto |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| AI agent development | ✓ | ✗ |
| MLOps & deployment | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Data engineering | ✗ | ✓ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Forward-deployed engineers | ✗ | ✗ |
| Access to a wider AI talent network | ✗ | ✗ |
Tech stack comparison: Vstorm vs Addepto
| Framework / platform | Vstorm | Addepto |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
Pricing comparison: Vstorm vs Addepto
| Criterion | Vstorm | Addepto |
|---|---|---|
| Minimum engagement | $10,000+ (Clutch) | Not published |
| Engagement models | Embedded team, Dedicated engineers, Project delivery | Embedded 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 | Fintech & payments, SaaS, Professional services | Manufacturing, Automotive, Retail |
| Best use cases | Rescuing an agent rollout that keeps failing in production, Embedding a tech lead and two engineers for a quarter | Adding Databricks engineers to a manufacturer's data team, Building a GenAI assistant for automotive service documents |
| Typical project type | Embedded team | Embedded team |
Vstorm vs Addepto: pros and cons
| Vstorm | |
|---|---|
| + | Agent reliability is its main specialty |
| + | Embedded package includes a tech lead, so you get engineering leadership too |
| + | Clutch data shows 45+ clients across 9 countries |
| - | A bench of about 25 engineers limits how many people it can place at once |
| - | Hourly rates are at the upper end for a Polish firm |
| - | Narrow focus on agents; classic ML or computer-vision staffing is a weaker fit |
| Addepto | |
|---|---|
| + | Nearly the whole team is AI engineers, according to its CEO |
| + | Industrial and automotive client experience |
| + | KMS ownership adds broader engineering capacity behind it |
| - | Acquired by KMS Technology in December 2025; ownership changes can bring new contract terms |
| - | Prefers joint delivery to straight staff placement |
| - | Team size estimates range from 8 to 99 |
Who should choose Vstorm?
A typical fit: rescuing an agent rollout that keeps failing in production.
Senior agent engineers who join an existing team to fix reliability and integration. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Fintech & payments, SaaS, Professional services.
Who should choose Addepto?
A typical fit: adding Databricks engineers to a manufacturer's data team.
AI-heavy team with manufacturing domain experience, now backed by a larger group. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Automotive, Retail, Aviation.
Decision matrix: Vstorm vs Addepto
| Your situation | Recommended choice |
|---|---|
| You need one AI specialist part-time | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Both; Vstorm rates higher overall |
| 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+ (Clutch)) vs Addepto (Not published) |
| You need engineers deployed inside your organization | Both; Vstorm rates higher overall |
| You need specialist depth in a specific vertical | Addepto |
Use case fit: Vstorm vs Addepto
| Use case | Vstorm fit | Addepto fit | Winner |
|---|---|---|---|
| Rescuing an agent rollout that keeps failing in production | Strong | Limited | Vstorm |
| Embedding a tech lead and two engineers for a quarter | Strong | Limited | Vstorm |
| Adding Databricks engineers to a manufacturer's data team | Strong | Strong | Both equally |
| Building a GenAI assistant for automotive service documents | Limited | Strong | Addepto |
Verdict: Vstorm vs Addepto
Vstorm (4.0/5) is the stronger overall choice for most AI-Native Staff Augmentation projects. Senior agent engineers who join an existing team to fix reliability and integration.
Addepto (3.9/5) is worth a look if you need building a GenAI assistant for automotive service documents. If your situation matches that, Addepto is a competitive option.
Related comparisons
Vstorm vs Addepto FAQ
Is Vstorm better than Addepto?
Vstorm (4.0/5) scores higher overall, but "better" depends on your use case. Vstorm's strongest advantage: agent reliability is its main specialty. Addepto's strongest advantage: nearly the whole team is AI engineers, according to its CEO.
How do Vstorm and Addepto differ in pricing?
Vstorm uses monthly agentic-engineering retainer or 3+ month embedded package; $100–$149/hr (clutch band) pricing with a minimum engagement of $10,000+ (Clutch). Addepto uses collaborative team model or managed delivery; 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: senior agent engineers who join an existing team to fix reliability and integration. Addepto's primary differentiator is: AI-heavy team with manufacturing domain experience, now backed by a larger group. They also differ in team size (40+ (25+ AI engineers per company) vs 50–99 (directory estimate)), minimum engagement ($10,000+ (Clutch) vs Not published), and primary industries served (Fintech & payments, SaaS vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.