Addepto vs Yalantis: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.3/5) edges ahead of Yalantis (4.0/5) overall. Addepto is the better choice for companies seeking a Forbes/Deloitte-recognized AI consultancy, provided they factor in post-acquisition integration risk.. Yalantis is the stronger option for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Yalantis: head-to-head summary
| Criterion | Addepto | Yalantis |
|---|---|---|
| Founded | 2018 | 2008 |
| HQ | Warsaw, Poland | Larnaca, Cyprus |
| Team size | 50–100 | 500+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Best for | Companies seeking a Forbes/Deloitte-recognized AI consultancy, provided they factor in post-acquisition integration risk. | Compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms. |
| Pricing model | Project-based, consulting retainer | Fixed project, dedicated team |
| Min. engagement | Not published | $10,000 |
| Primary tech stack | Python, TensorFlow, AWS | AWS SageMaker, Azure ML, Google Cloud Vertex AI |
| Industries served | FinTech, Manufacturing, Retail & E-commerce | Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain |
Addepto vs Yalantis: overview
Addepto
Addepto was founded in Warsaw in 2018 by Data Science enthusiasts Edwin Lisowski and Artur Haponik, delivering AI consulting and data-driven solutions recognized by Forbes, Deloitte, and the Financial Times. In December 2025, Addepto was acquired by KMS Technology, and prospective clients should confirm how delivery teams, pricing, and leadership continuity have changed post-acquisition. Reported employee counts vary from roughly 11–50 to 72, reflecting the transition period around the acquisition.
Yalantis
Yalantis was founded in 2008 with headquarters in Larnaca, Cyprus and development hubs in Dnipro, Kyiv, and Lviv, Ukraine, growing to roughly 500 specialists. The firm positions itself as a 'compliance-first engineering partner,' building high-performance ML models across Amazon, Microsoft Azure, and Google Cloud ML platforms, including data preparation, model selection, training, deployment, and multimodal LLM processing for visual and text data. Project costs are reported to range from $10,000 to over $800,000, indicating the firm handles both small scoped projects and large enterprise programs.
Services and capabilities: Addepto vs Yalantis
| Capability | Addepto | Yalantis |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✓ | ✗ |
Tech stack comparison: Addepto vs Yalantis
| Framework / platform | Addepto | Yalantis |
|---|---|---|
| TensorFlow | ✓ | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | ✓ |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Addepto vs Yalantis
| Criterion | Addepto | Yalantis |
|---|---|---|
| Minimum engagement | Not published | $10,000 |
| Engagement models | Project-based, Consulting retainer | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Accessible |
Target audience comparison: Addepto vs Yalantis
| Dimension | Addepto | Yalantis |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Manufacturing, Retail & E-commerce | Healthcare, IoT & Embedded Systems, FinTech |
| Best use cases | Company wants an AI consultancy with independent press recognition for vendor due diligence., Client is comfortable evaluating a firm mid-acquisition and confirming continuity directly before signing. | Healthcare or IoT company needs ML development from a compliance-first engineering partner., Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. |
| Typical project type | Project-based | Fixed project |
Addepto vs Yalantis: pros and cons
| Addepto | |
|---|---|
| + | Press recognition from Forbes, Deloitte, and the Financial Times provides independent third-party validation beyond client testimonials. |
| + | Founder-led AI consulting model since 2018, prior to being acquired. |
| + | Now backed by KMS Technology's broader resources post-acquisition, which may add delivery capacity. |
| - | Acquired by KMS Technology in December 2025 — leadership continuity, pricing, and delivery-team stability during integration are unconfirmed. |
| - | Reported headcount varies significantly across sources (11–50 vs. 72), making current team size hard to pin down. |
| - | Recent acquisition means the company's standalone track record may not reflect how engagements are run going forward. |
| Yalantis | |
|---|---|
| + | Compliance-first positioning is a genuine differentiator for regulated industries like healthcare and embedded/IoT systems. |
| + | Multi-cloud ML delivery capability (AWS, Azure, GCP) avoids vendor lock-in to a single hyperscaler. |
| + | Wide project-cost range ($10,000–$800,000+) means the firm can serve both small scoped projects and large programs without switching vendors. |
| + | 500+ specialists across three Ukrainian development hubs provides meaningful delivery redundancy. |
| - | IoT and hardware engineering heritage means ML is one of several engineering disciplines rather than the firm's sole focus. |
| - | Larnaca, Cyprus legal HQ with all technical delivery in Ukraine is standard for the region but worth confirming for contract jurisdiction purposes. |
Who should choose Addepto?
Addepto is the right choice for companies seeking a Forbes/Deloitte-recognized AI consultancy, provided they factor in post-acquisition integration risk..
AI consulting boutique with third-party press recognition (Forbes, Deloitte, Financial Times), now part of KMS Technology.. Minimum engagement starts at Not published. Works best with clients in FinTech, Manufacturing, Retail & E-commerce.
Who should choose Yalantis?
Yalantis is the right choice for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..
Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof.. Minimum engagement starts at $10,000. Works best with clients in Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain.
Decision matrix: Addepto vs Yalantis
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Yalantis |
| You need a large dedicated team for an ongoing programme | Yalantis |
| Your budget is at the lower end | Compare: Addepto (Not published) vs Yalantis ($10,000) |
| You need specialist depth in a specific vertical | Yalantis |
| You need production MLOps support after model launch | Yalantis |
| You need consulting before committing to a build | Addepto |
Use case fit: Addepto vs Yalantis
| Use case | Addepto fit | Yalantis fit | Winner |
|---|---|---|---|
| Company wants an AI consultancy with independent press recognition for vendor due diligence. | Strong | Strong | Both equally |
| Client is comfortable evaluating a firm mid-acquisition and confirming continuity directly before signing. | Strong | Limited | Addepto |
| Healthcare or IoT company needs ML development from a compliance-first engineering partner. | Limited | Strong | Yalantis |
| Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. | Strong | Strong | Both equally |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: Addepto vs Yalantis
Addepto (4.3/5) is the stronger overall choice for most Machine Learning Development projects. AI consulting boutique with third-party press recognition (Forbes, Deloitte, Financial Times), now part of KMS Technology.. It is best for companies seeking a Forbes/Deloitte-recognized AI consultancy, provided they factor in post-acquisition integration risk..
Yalantis (4.0/5) is the better choice when compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. If your situation matches those criteria, Yalantis is a competitive option.
Related comparisons
Addepto vs Yalantis FAQ
Is Addepto better than Yalantis?
Addepto (4.3/5) scores higher overall, but "better" depends on your use case. Addepto is better for companies seeking a Forbes/Deloitte-recognized AI consultancy, provided they factor in post-acquisition integration risk.. Yalantis is better for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..
How do Addepto and Yalantis differ in pricing?
Addepto uses project-based, consulting retainer pricing with a minimum engagement of Not published. Yalantis uses fixed project, dedicated team pricing with a minimum engagement of $10,000. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or Yalantis?
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 Yalantis?
Addepto's primary differentiator is: ai consulting boutique with third-party press recognition (forbes, deloitte, financial times), now part of kms technology.. Yalantis's primary differentiator is: compliance-first positioning combined with multi-cloud ml delivery (aws, azure, gcp) under one roof.. They also differ in team size (50–100 vs 500+), minimum engagement (Not published vs $10,000), and primary industries served (FinTech, Manufacturing vs Healthcare, IoT & Embedded Systems).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.