DataRoot Labs vs Addepto: full comparison for 2026
Last updated: July 2026
Quick verdict
DataRoot Labs (4.6/5) edges ahead of Addepto (4.4/5) overall. DataRoot Labs is the better choice for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects.. Addepto is the stronger option for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build.. The right choice depends on your project size, budget, and required tech stack.
DataRoot Labs vs Addepto: head-to-head summary
| Criterion | DataRoot Labs | Addepto |
|---|---|---|
| Founded | 2016 | 2018 |
| HQ | Kyiv, Ukraine | Warsaw, Poland |
| Team size | 51–200 | 51–200 |
| Rating | 4.6 / 5 | 4.4 / 5 |
| Best for | Startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects. | Cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build. |
| Pricing model | Time & Material, project-based | Project-based |
| Min. engagement | $10,000+ | $10,000 |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, MLOps tooling, Cloud ML platforms (AWS/GCP/Azure) |
| Industries served | E-commerce, Healthcare, Enterprise software, Robotics | Finance, Healthcare, Retail |
DataRoot Labs vs Addepto: overview
DataRoot Labs
DataRoot Labs is a Ukraine-founded machine learning consultancy established in 2016 that has remained AI/ML-only since inception, in contrast to firms that added AI as a service line later. The company offers AI consulting, custom model development and training, solution architecture, and deployment/monitoring, with stated specializations in large language model fine-tuning, computer vision, reinforcement learning, and vector databases. Publicly named clients include OLX, IBM, Databand, and Moxie (Embodied). The company also runs DataRoot University, a training program it states has produced over 6,000 machine learning graduates (per company website; independently unverifiable), which functions as a talent pipeline and community credibility signal.
Addepto
Addepto is a Poland-based AI consulting firm founded in 2018 by Artur Haponik and Edwin Lisowski that focuses specifically on machine learning consulting, MLOps consulting, and data/analytics advisory work rather than broader software development. The company has around 52 employees and holds a 4.7 Clutch rating, with Clutch-reported project costs typically in the $10,000–$49,000 range, making it one of the more budget-accessible options among firms in this category. Addepto has been recognized among Forbes' top AI consulting companies and appeared on the Deloitte Technology Fast 500 EMEA list, citing 1,193 percent revenue growth over the qualifying period. In December 2025, Addepto was acquired by KMS Technology, a US-based digital engineering, data, and AI company backed by growth private equity firm Sunstone Partners; Addepto now operates as an integrated division rather than as a fully independent company.
Services and capabilities: DataRoot Labs vs Addepto
| Capability | DataRoot Labs | Addepto |
|---|---|---|
| Custom model training | ✓ | ✓ |
| Fine-tuning & adaptation | ✓ | ✗ |
| MLOps pipeline | ✗ | ✓ |
| Model deployment & serving | ✓ | ✗ |
| Data engineering for ML | ✗ | ✓ |
| ML infrastructure management | ✗ | ✗ |
| Computer vision | ✓ | ✗ |
| NLP & LLM development | ✓ | ✗ |
| Forecasting & time-series modeling | ✗ | ✗ |
| ML strategy consulting | ✗ | ✓ |
Tech stack comparison: DataRoot Labs vs Addepto
| Framework / platform | DataRoot Labs | Addepto |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Amazon Bedrock | N/A | N/A |
| Google Cloud | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Kubernetes | ✓ | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: DataRoot Labs vs Addepto
| Criterion | DataRoot Labs | Addepto |
|---|---|---|
| Minimum engagement | $10,000+ | $10,000 |
| Engagement models | Time & Material, Fixed project, Dedicated team | Fixed project, Advisory/consulting retainer |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: DataRoot Labs vs Addepto
| Dimension | DataRoot Labs | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | E-commerce, Healthcare, Enterprise software | Finance, Healthcare, Retail |
| Best use cases | Fine-tuning an open-source LLM for a domain-specific internal tool, Building a computer vision model for retail or logistics quality inspection | Auditing an existing ML pipeline and recommending MLOps improvements, Running a well-scoped, budget-constrained machine learning pilot |
| Typical project type | Time & Material | Fixed project |
DataRoot Labs vs Addepto: pros and cons
| DataRoot Labs | |
|---|---|
| + | Clutch rating of 4.9/5 across 23 verified reviews, among the highest in this comparison set. |
| + | Named, checkable clients (OLX, IBM, Databand, Moxie) rather than anonymized case studies only. |
| + | Full IP transfer to clients is cited as standard practice in reviews. |
| + | AI-only focus since 2016 avoids the generalist dilution seen in broader software houses. |
| - | Small team (51–200) constrains capacity for large, multi-team enterprise rollouts. |
| - | Delivery is concentrated in Ukraine, which some risk-averse enterprise buyers may flag for business-continuity planning. |
| - | Public tech-stack disclosure is limited beyond high-level specialization claims. |
| - | Minimum engagement of $10K+ is accessible, but larger programs will need custom scoping not published on the site. |
| Addepto | |
|---|---|
| + | 4.7 Clutch rating with lower typical project cost ($10K–$49K) than most peers in this comparison. |
| + | Named a top 10 AI consulting company by Forbes. |
| + | Deloitte Technology Fast 500 EMEA recognition (#143) signals strong recent revenue growth. |
| + | Focused specifically on ML/MLOps consulting rather than diluting attention across general software development. |
| - | Small team (~52 employees) caps capacity for large or multiple concurrent enterprise engagements. |
| - | Lower typical project size may signal a fit for smaller-scope work rather than large production ML platforms. |
| - | Public case studies with named enterprise clients are limited in available sources. |
| - | Now part of KMS Technology following the December 2025 acquisition, introducing near-term integration and roadmap uncertainty for prospective clients. |
Who should choose DataRoot Labs?
DataRoot Labs is the right choice for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects..
Has never diversified beyond AI/ML services, and backs its delivery bench with an in-house ML training program (DataRoot University).. Minimum engagement starts at $10,000+. Works best with clients in E-commerce, Healthcare, Enterprise software, Robotics.
Who should choose Addepto?
Addepto is the right choice for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build..
Dedicated MLOps-consulting service line and Clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option.. Minimum engagement starts at $10,000. Works best with clients in Finance, Healthcare, Retail.
Decision matrix: DataRoot Labs vs Addepto
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | DataRoot Labs |
| You need a large dedicated team for an ongoing programme | DataRoot Labs |
| Your budget is at the lower end | DataRoot Labs |
| You need specialist depth in a specific vertical | DataRoot Labs |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Addepto |
Use case fit: DataRoot Labs vs Addepto
| Use case | DataRoot Labs fit | Addepto fit | Winner |
|---|---|---|---|
| Fine-tuning an open-source LLM for a domain-specific internal tool | Strong | Limited | DataRoot Labs |
| Building a computer vision model for retail or logistics quality inspection | Strong | Limited | DataRoot Labs |
| Auditing an existing ML pipeline and recommending MLOps improvements | Limited | Strong | Addepto |
| Running a well-scoped, budget-constrained machine learning pilot | Limited | Strong | Addepto |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Limited | Strong | Addepto |
Verdict: DataRoot Labs vs Addepto
DataRoot Labs (4.6/5) is the stronger overall choice for most ML Model Development projects. Has never diversified beyond AI/ML services, and backs its delivery bench with an in-house ML training program (DataRoot University).. It is best for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects..
Addepto (4.4/5) is the better choice when cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build.. If your situation matches those criteria, Addepto is a competitive option.
Related comparisons
DataRoot Labs vs Addepto FAQ
Is DataRoot Labs better than Addepto?
DataRoot Labs (4.6/5) scores higher overall, but "better" depends on your use case. DataRoot Labs is better for startups and mid-market companies wanting a senior, AI-only team for LLM fine-tuning, computer vision, or reinforcement-learning projects.. Addepto is better for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build..
How do DataRoot Labs and Addepto differ in pricing?
DataRoot Labs uses time & material, project-based pricing with a minimum engagement of $10,000+. Addepto uses project-based 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: DataRoot Labs or Addepto?
DataRoot Labs 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 DataRoot Labs and Addepto?
DataRoot Labs's primary differentiator is: has never diversified beyond ai/ml services, and backs its delivery bench with an in-house ml training program (dataroot university).. Addepto's primary differentiator is: dedicated mlops-consulting service line and clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option.. They also differ in team size (51–200 vs 51–200), minimum engagement ($10,000+ vs $10,000), and primary industries served (E-commerce, Healthcare vs Finance, Healthcare).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.