Addepto vs LTIMindtree: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of LTIMindtree (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.. LTIMindtree is the stronger option for large enterprises, particularly in BFSI and technology/media sectors, wanting dedicated ModelOps and model-governance tooling from a Larsen & Toubro-backed vendor.. The right choice depends on your project size, budget, and required tech stack.
Addepto vs LTIMindtree: head-to-head summary
| Criterion | Addepto | LTIMindtree |
|---|---|---|
| Founded | 2018 | 1996 |
| HQ | Warsaw, Poland | Mumbai, India |
| 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, particularly in BFSI and technology/media sectors, wanting dedicated ModelOps and model-governance tooling from a Larsen & Toubro-backed vendor. |
| 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 SageMaker, Amazon Comprehend, Amazon Rekognition |
| Industries served | Finance, Healthcare, Retail | Banking, financial services and insurance, Technology, media and telecom |
Addepto vs LTIMindtree: 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.
LTIMindtree
LTIMindtree was formed through the November 2022 merger of L&T Infotech (originally incorporated in 1996 as a Larsen & Toubro subsidiary) and Mindtree, and is headquartered in Mumbai, India, with roughly 84,000 to 88,000 employees. Its AI Engineering @ Scale practice includes ModelOps templates, model governance and responsible AI tooling, and model-monitoring feedback loops built on AWS services including SageMaker, Comprehend, Rekognition, and Textract, alongside a Google Cloud AI engineering practice and an LTIMindtree-IBM watsonx Center of Excellence for generative AI. Named client work includes onsemi's AI chatbot implementation, presented at Oracle AI World 2025.
Services and capabilities: Addepto vs LTIMindtree
| Capability | Addepto | LTIMindtree |
|---|---|---|
| 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 LTIMindtree
| Framework / platform | Addepto | LTIMindtree |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | ✓ |
| Amazon Bedrock | N/A | N/A |
| Google Cloud | N/A | ✓ |
| Microsoft Azure | N/A | N/A |
| Kubernetes | N/A | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: Addepto vs LTIMindtree
| Criterion | Addepto | LTIMindtree |
|---|---|---|
| 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 LTIMindtree
| Dimension | Addepto | LTIMindtree |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Finance, Healthcare, Retail | Banking, financial services and insurance, Technology, media and telecom |
| Best use cases | Auditing an existing ML pipeline and recommending MLOps improvements, Running a well-scoped, budget-constrained machine learning pilot | Implementing model governance and responsible AI tooling for a regulated enterprise (e.g., BFSI), Deploying models across AWS (SageMaker, Comprehend, Rekognition, Textract) with named ModelOps templates |
| Typical project type | Fixed project | Enterprise project engagement |
Addepto vs LTIMindtree: 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. |
| LTIMindtree | |
|---|---|
| + | Named, productized ModelOps templates and responsible-AI/model-governance tooling, more specific than generic MLOps claims. |
| + | Dedicated LTIMindtree-IBM watsonx Center of Excellence for generative AI adds a named technology partnership. |
| + | Named client case study (onsemi AI chatbot, presented at Oracle AI World 2025). |
| + | Backed by the Larsen & Toubro Group, providing financial and operational stability. |
| - | Post-merger brand integration (L&T Infotech + Mindtree) is still relatively recent, which may create some organizational transition friction. |
| - | No clearly located aggregate Clutch/G2 star rating specific to its AI practice in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | Very large scale means ML/AI is one of many practice areas competing for delivery attention. |
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 LTIMindtree?
LTIMindtree is the right choice for large enterprises, particularly in BFSI and technology/media sectors, wanting dedicated ModelOps and model-governance tooling from a Larsen & Toubro-backed vendor..
Explicit ModelOps templates and model-governance/responsible-AI tooling as named, productized capabilities rather than only bespoke consulting delivery, backed by an IBM watsonx Center of Excellence.. Minimum engagement starts at Not published. Works best with clients in Banking, financial services and insurance, Technology, media and telecom.
Decision matrix: Addepto vs LTIMindtree
| 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 LTIMindtree (Not published) |
| You need specialist depth in a specific vertical | Addepto |
| 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 LTIMindtree
| Use case | Addepto fit | LTIMindtree 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 |
| Implementing model governance and responsible AI tooling for a regulated enterprise (e.g., BFSI) | Limited | Strong | LTIMindtree |
| Deploying models across AWS (SageMaker, Comprehend, Rekognition, Textract) with named ModelOps templates | Limited | Strong | LTIMindtree |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Strong | Limited | Addepto |
Verdict: Addepto vs LTIMindtree
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..
LTIMindtree (3.9/5) is the better choice when large enterprises, particularly in BFSI and technology/media sectors, wanting dedicated ModelOps and model-governance tooling from a Larsen & Toubro-backed vendor.. If your situation matches those criteria, LTIMindtree is a competitive option.
Related comparisons
Addepto vs LTIMindtree FAQ
Is Addepto better than LTIMindtree?
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.. LTIMindtree is better for large enterprises, particularly in BFSI and technology/media sectors, wanting dedicated ModelOps and model-governance tooling from a Larsen & Toubro-backed vendor..
How do Addepto and LTIMindtree differ in pricing?
Addepto uses project-based pricing with a minimum engagement of $10,000. LTIMindtree 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 LTIMindtree?
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 LTIMindtree?
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.. LTIMindtree's primary differentiator is: explicit modelops templates and model-governance/responsible-ai tooling as named, productized capabilities rather than only bespoke consulting delivery, backed by an ibm watsonx center of excellence.. 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 Banking, financial services and insurance, Technology, media and telecom).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.