Sigmoid vs Addepto: full comparison for 2026
Last updated: July 2026
Quick verdict
Sigmoid (4.2/5) edges ahead of Addepto (4.1/5) overall. Sigmoid is the better choice for large enterprises needing a data-engineering-first partner that also builds the ML models sitting on top of that data.. Addepto is the stronger option for companies wanting boutique AI/BI consulting from a team now backed by KMS Technology's additional resources post-acquisition.. The right choice depends on your project size, budget, and required tech stack.
Sigmoid vs Addepto: head-to-head summary
| Criterion | Sigmoid | Addepto |
|---|---|---|
| Founded | 2013 | 2018 |
| HQ | Bengaluru, India / New York, USA | Warsaw, Poland |
| Team size | 501–1,000 | 51–200 |
| Rating | 4.2 / 5 | 4.1 / 5 |
| Best for | Large enterprises needing a data-engineering-first partner that also builds the ML models sitting on top of that data. | Companies wanting boutique AI/BI consulting from a team now backed by KMS Technology's additional resources post-acquisition. |
| Pricing model | Managed services and fixed project | Fixed project and consulting retainer |
| Min. engagement | Not published | $20K |
| Primary tech stack | Python, Apache Spark, Databricks | Python, Scikit-learn, TensorFlow |
| Industries served | Retail, Technology/SaaS, Financial Services, Media | Financial Services, Retail, Manufacturing |
Sigmoid vs Addepto: overview
Sigmoid
Sigmoid is a data engineering and AI consulting firm founded in 2013 by Rahul Singh, Lokesh Anand, and Mayur Rustagi. Sources differ on its primary headquarters, with some citing Bengaluru, India and others New York; reported headcount ranges from roughly 600 to 760 employees. The firm markets itself around round-the-clock data engineering and AI services for more than 25 Fortune 500 clients.
Addepto
Addepto is an AI and data consulting company founded in Warsaw, Poland in 2018 by Edwin Lisowski and Artur Haponik (one source lists 2017), specializing in machine learning, artificial intelligence, and business intelligence solutions. Reported headcount is roughly 55–58 employees across Europe, North America, and Asia. In December 2025, Addepto was acquired by KMS Technology; prospective clients should confirm how the acquisition affects team continuity, existing contracts, and service delivery going forward.
Services and capabilities: Sigmoid vs Addepto
| Capability | Sigmoid | Addepto |
|---|---|---|
| Custom ML model development | ✓ | ✓ |
| Deep learning & computer vision | ✗ | ✗ |
| NLP & LLM / Generative AI | ✗ | ✗ |
| MLOps & production deployment | ✗ | ✗ |
| Data engineering | ✓ | ✗ |
| AI strategy consulting | ✗ | ✓ |
| Staff augmentation | ✗ | ✗ |
Tech stack comparison: Sigmoid vs Addepto
| Framework / platform | Sigmoid | Addepto |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | ✓ |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | ✓ | N/A |
| LangChain | N/A | N/A |
Pricing comparison: Sigmoid vs Addepto
| Criterion | Sigmoid | Addepto |
|---|---|---|
| Minimum engagement | Not published | $20K |
| Engagement models | Managed services, Fixed project | Fixed project, Consulting retainer |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Enterprise / not published | Accessible |
Target audience comparison: Sigmoid vs Addepto
| Dimension | Sigmoid | Addepto |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Retail, Technology/SaaS, Financial Services | Financial Services, Retail, Manufacturing |
| Best use cases | Building the data pipeline and the ML model together for a large enterprise client, Fortune 500 programs needing 24/7 delivery across time zones | Mid-market companies wanting boutique AI/BI consulting now paired with KMS Technology's broader resources, Business intelligence projects that also require a machine learning component |
| Typical project type | Managed services | Fixed project |
Sigmoid vs Addepto: pros and cons
| Sigmoid | |
|---|---|
| + | Round-the-clock delivery model across geographies and time zones supports faster iteration |
| + | 25+ named Fortune 500 clients suggests real enterprise-scale delivery credibility |
| + | Combines data engineering and AI/ML under one roof, reducing hand-off friction |
| + | 12 years of focused operation in data engineering and analytics |
| - | Public sources disagree on primary headquarters location (Bengaluru vs. New York) — confirm the contracting entity directly |
| - | Data-engineering-first positioning may mean less emphasis on cutting-edge model research than AI-first boutiques |
| - | Minimum engagement size not publicly disclosed |
| Addepto | |
|---|---|
| + | 7 years of focused AI/BI consulting experience prior to the KMS Technology acquisition |
| + | Small team size historically meant direct founder-level access on engagements |
| + | Multi-continent presence (Europe, North America, Asia) despite a compact headcount |
| + | Acquisition by KMS Technology (Dec 2025) may bring additional delivery resources and stability |
| - | Acquired by KMS Technology in December 2025 — buyers should confirm how this affects team continuity, pricing, and existing contracts before signing |
| - | Public sources disagree on exact founding year (2017 vs. 2018) and employee count (55 vs. 58) |
| - | Post-acquisition integration could change the service delivery model in ways not yet publicly documented |
Who should choose Sigmoid?
Sigmoid is the right choice for large enterprises needing a data-engineering-first partner that also builds the ML models sitting on top of that data..
Data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages.. Minimum engagement starts at Not published. Works best with clients in Retail, Technology/SaaS, Financial Services, Media.
Who should choose Addepto?
Addepto is the right choice for companies wanting boutique AI/BI consulting from a team now backed by KMS Technology's additional resources post-acquisition..
Boutique AI/BI consultancy that gained additional scale and resources through its December 2025 acquisition by KMS Technology.. Minimum engagement starts at $20K. Works best with clients in Financial Services, Retail, Manufacturing.
Decision matrix: Sigmoid vs Addepto
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Sigmoid |
| You need a large dedicated team for an ongoing programme | Check each company's engagement model |
| Your budget is at the lower end | Compare: Sigmoid (Not published) vs Addepto ($20K) |
| You need specialist depth in a specific vertical | Sigmoid |
| 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: Sigmoid vs Addepto
| Use case | Sigmoid fit | Addepto fit | Winner |
|---|---|---|---|
| Building the data pipeline and the ML model together for a large enterprise client | Strong | Limited | Sigmoid |
| Fortune 500 programs needing 24/7 delivery across time zones | Strong | Limited | Sigmoid |
| Mid-market companies wanting boutique AI/BI consulting now paired with KMS Technology's broader resources | Limited | Strong | Addepto |
| Business intelligence projects that also require a machine learning component | Limited | Strong | Addepto |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Sigmoid vs Addepto
Sigmoid (4.2/5) is the stronger overall choice for most Machine Learning Development projects. Data-engineering-first delivery model, with ML/AI built directly on pipelines the firm also builds and manages.. It is best for large enterprises needing a data-engineering-first partner that also builds the ML models sitting on top of that data..
Addepto (4.1/5) is the better choice when companies wanting boutique AI/BI consulting from a team now backed by KMS Technology's additional resources post-acquisition.. If your situation matches those criteria, Addepto is a competitive option.
Related comparisons
Sigmoid vs Addepto FAQ
Is Sigmoid better than Addepto?
Sigmoid (4.2/5) scores higher overall, but "better" depends on your use case. Sigmoid is better for large enterprises needing a data-engineering-first partner that also builds the ML models sitting on top of that data.. Addepto is better for companies wanting boutique AI/BI consulting from a team now backed by KMS Technology's additional resources post-acquisition..
How do Sigmoid and Addepto differ in pricing?
Sigmoid uses managed services and fixed project pricing with a minimum engagement of Not published. Addepto uses fixed project and consulting retainer pricing with a minimum engagement of $20K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Sigmoid or Addepto?
Sigmoid is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Sigmoid and Addepto?
Sigmoid's primary differentiator is: data-engineering-first delivery model, with ml/ai built directly on pipelines the firm also builds and manages.. Addepto's primary differentiator is: boutique ai/bi consultancy that gained additional scale and resources through its december 2025 acquisition by kms technology.. They also differ in team size (501–1,000 vs 51–200), minimum engagement (Not published vs $20K), and primary industries served (Retail, Technology/SaaS vs Financial Services, Retail).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.