Addepto vs Cognizant: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of Cognizant (3.9/5) overall. Addepto is the better 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.. Cognizant is the stronger option for large enterprises, especially in healthcare, wanting a very large AI/analytics consulting bench with a dedicated industry-specific MLOps platform.. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Cognizant: head-to-head summary
| Criterion | Addepto | Cognizant |
|---|---|---|
| Founded | 2018 | 1994 |
| HQ | Warsaw, Poland | Teaneck, USA |
| Team size | 51–200 | 10,000+ |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Best for | Cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build. | Large enterprises, especially in healthcare, wanting a very large AI/analytics consulting bench with a dedicated industry-specific MLOps platform. |
| Pricing model | Project-based | Not published; enterprise project engagements |
| Min. engagement | $10,000 | Not published |
| Primary tech stack | Python, MLOps tooling, Cloud ML platforms (AWS/GCP/Azure) | AWS, MLOps platform (proprietary, healthcare-focused), Python |
| Industries served | Finance, Healthcare, Retail | Healthcare, Financial services, Insurance, Retail |
Addepto vs Cognizant: overview
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.
Cognizant
Cognizant Technology Solutions was founded in 1994 and is headquartered in Teaneck, New Jersey, trading publicly on NASDAQ under CTSH. The company reports delivering ML and MLOps services through roughly 23,000 data, analytics, and AI consultants, including about 7,000 specialists and 800 data scientists, and maintains a dedicated MLOps platform offering specifically for healthcare. Cognizant is also the parent company of Devbridge, a Chicago-founded product engineering boutique acquired in December 2021, whose digital engineering capabilities (including ML) were folded into Cognizant's broader delivery network.
Services and capabilities: Addepto vs Cognizant
| Capability | Addepto | Cognizant |
|---|---|---|
| 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: Addepto vs Cognizant
| Framework / platform | Addepto | Cognizant |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | 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: Addepto vs Cognizant
| Criterion | Addepto | Cognizant |
|---|---|---|
| Minimum engagement | $10,000 | Not published |
| Engagement models | Fixed project, Advisory/consulting retainer | Enterprise project engagement, Managed AI services |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Addepto vs Cognizant
| Dimension | Addepto | Cognizant |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Finance, Healthcare, Retail | Healthcare, Financial services, Insurance |
| Best use cases | Auditing an existing ML pipeline and recommending MLOps improvements, Running a well-scoped, budget-constrained machine learning pilot | Healthcare organizations needing a dedicated MLOps platform tailored to clinical or health-data workflows, Very large enterprises needing a substantial, always-available data/AI consulting bench |
| Typical project type | Fixed project | Enterprise project engagement |
Addepto vs Cognizant: pros and cons
| 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. |
| Cognizant | |
|---|---|
| + | Very large disclosed data/AI consulting bench (23,000+ consultants, 800 data scientists) provides substantial delivery depth. |
| + | Named, industry-specific MLOps platform for healthcare rather than only generic horizontal tooling. |
| + | Publicly traded (NASDAQ: CTSH) with strong financial transparency. |
| + | AWS partner status supports certified cloud-native ML delivery. |
| - | Very large, generalist IT services brand means ML/AI delivery quality can vary significantly by account team. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its AI/ML practice in available public sources (parent-company G2 rating around 4.2 reflects the broader business, not ML specifically). |
| - | Pricing model and minimum engagement are not published, and typical minimums are substantial for enterprise engagements. |
| - | The 2021 Devbridge acquisition means clients seeking that boutique's original independent culture will instead get Cognizant's larger delivery structure. |
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.
Who should choose Cognizant?
Cognizant is the right choice for large enterprises, especially in healthcare, wanting a very large AI/analytics consulting bench with a dedicated industry-specific MLOps platform..
Dedicated, named MLOps platform specifically built for healthcare, combined with one of the largest disclosed data/AI consultant headcounts (23,000+) in this comparison.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Financial services, Insurance, Retail.
Decision matrix: Addepto vs Cognizant
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Addepto |
| You need a large dedicated team for an ongoing programme | Check each company's engagement model |
| Your budget is at the lower end | Compare: Addepto ($10,000) vs Cognizant (Not published) |
| You need specialist depth in a specific vertical | Cognizant |
| 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: Addepto vs Cognizant
| Use case | Addepto fit | Cognizant fit | Winner |
|---|---|---|---|
| Auditing an existing ML pipeline and recommending MLOps improvements | Strong | Limited | Addepto |
| Running a well-scoped, budget-constrained machine learning pilot | Strong | Limited | Addepto |
| Healthcare organizations needing a dedicated MLOps platform tailored to clinical or health-data workflows | Limited | Strong | Cognizant |
| Very large enterprises needing a substantial, always-available data/AI consulting bench | Limited | Strong | Cognizant |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Strong | Both equally |
Verdict: Addepto vs Cognizant
Addepto (4.4/5) is the stronger overall choice for most ML Model Development projects. Dedicated MLOps-consulting service line and Clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option.. It is best for cost-conscious teams that specifically need MLOps consulting or a well-scoped machine learning advisory engagement rather than a full custom software build..
Cognizant (3.9/5) is the better choice when large enterprises, especially in healthcare, wanting a very large AI/analytics consulting bench with a dedicated industry-specific MLOps platform.. If your situation matches those criteria, Cognizant is a competitive option.
Related comparisons
Addepto vs Cognizant FAQ
Is Addepto better than Cognizant?
Addepto (4.4/5) scores higher overall, but "better" depends on your use case. 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.. Cognizant is better for large enterprises, especially in healthcare, wanting a very large AI/analytics consulting bench with a dedicated industry-specific MLOps platform..
How do Addepto and Cognizant differ in pricing?
Addepto uses project-based pricing with a minimum engagement of $10,000. Cognizant uses not published; enterprise project engagements pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or Cognizant?
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 Cognizant?
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.. Cognizant's primary differentiator is: dedicated, named mlops platform specifically built for healthcare, combined with one of the largest disclosed data/ai consultant headcounts (23,000+) in this comparison.. They also differ in team size (51–200 vs 10,000+), minimum engagement ($10,000 vs Not published), and primary industries served (Finance, Healthcare vs Healthcare, Financial services).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.