Markovate vs ScienceSoft: full comparison for 2026
Last updated: July 2026
Quick verdict
Markovate (4.1/5) edges ahead of ScienceSoft (3.8/5) overall. Markovate is the better choice for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM).. ScienceSoft is the stronger option for enterprises wanting AI/MLOps delivery from a 35-year-old IT consultancy with an extensive multi-industry track record.. The right choice depends on your project size, budget, and required tech stack.
Markovate vs ScienceSoft: head-to-head summary
| Criterion | Markovate | ScienceSoft |
|---|---|---|
| Founded | 2015 | 1989 |
| HQ | San Francisco, California, United States | McKinney, Texas, United States |
| Team size | 50–100 | 750+ |
| Rating | 4.1 / 5 | 3.8 / 5 |
| Best for | Companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM). | Enterprises wanting AI/MLOps delivery from a 35-year-old IT consultancy with an extensive multi-industry track record. |
| Pricing model | Project-based, dedicated team | Time & materials, managed engagement |
| Min. engagement | Not published | Not published |
| Primary tech stack | LangChain, OpenAI API, Python | AWS, Azure ML, Google Cloud |
| Industries served | Healthcare, Retail & E-commerce, FinTech, Travel & Hospitality | Healthcare, Insurance, Manufacturing, Retail & E-commerce, Telecom |
Markovate vs ScienceSoft: overview
Markovate
Markovate was founded in 2015 and is led by CEO Rajeev Sharma, an AI veteran with 18+ years of experience who previously led AI initiatives at AT&T and IBM. Headquartered with a San Francisco address (some sources cite Toronto as an operating base), the company has grown to roughly 51 employees, including 50+ engineers described as 'certified AI engineers' (per company website), delivering custom AI agents, chatbot development, and cloud services for healthcare, retail, fintech, SaaS, and travel clients. Its small team size makes it a boutique play best suited to scoped generative AI or agent projects rather than large-scale programs.
ScienceSoft
ScienceSoft was founded in 1989 and is headquartered in McKinney, Texas, bringing together more than 750 engineers and consultants with a track record of over 4,200 successful projects for 1,400+ clients across healthcare, insurance, investment, manufacturing, retail, and telecom. Its AI practice includes AI engineers, generative AI consultants, and MLOps experts working with both open-source frameworks and cloud-native AI services, and Clutch has named ScienceSoft a 2018 Global IT Leader among its Clutch 1000 companies. At 35+ years old, it is one of the longest-established firms in this list, with AI as a newer addition to a much older core business.
Services and capabilities: Markovate vs ScienceSoft
| Capability | Markovate | ScienceSoft |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✓ |
Tech stack comparison: Markovate vs ScienceSoft
| Framework / platform | Markovate | ScienceSoft |
|---|---|---|
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | ✓ |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Markovate vs ScienceSoft
| Criterion | Markovate | ScienceSoft |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team | Managed engagement, Time & materials, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Markovate vs ScienceSoft
| Dimension | Markovate | ScienceSoft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Retail & E-commerce, FinTech | Healthcare, Insurance, Manufacturing |
| Best use cases | Company wants an AI agent or chatbot built by a team led by a former enterprise AI executive., Healthcare or fintech startup needs a scoped generative AI project from a small, focused vendor. | Enterprise wants AI/MLOps delivery from a vendor with 35+ years of institutional stability., Insurance or healthcare company needs a vendor with a very large (4,200+) project delivery track record. |
| Typical project type | Project-based | Managed engagement |
Markovate vs ScienceSoft: pros and cons
| Markovate | |
|---|---|
| + | CEO's 18+ years leading AI initiatives at AT&T and IBM brings genuine enterprise AI leadership experience to client engagements. |
| + | Focused service scope (AI agents, chatbots, generative AI) rather than a broad, diluted general-consulting offering. |
| + | Serves a wide industry spread (healthcare to travel) despite small team size, suggesting adaptable delivery patterns. |
| - | At roughly 51 employees, capacity for multiple concurrent large engagements is limited. |
| - | HQ location is inconsistently reported (San Francisco vs. Toronto across sources) — confirm the contracting entity directly. |
| - | "50+ certified AI engineers" claim on a 51-person total headcount is a company claim worth verifying during vendor due diligence. |
| ScienceSoft | |
|---|---|
| + | 35+ years of operating history (since 1989) is among the longest track records of any firm in this list. |
| + | 4,200+ successful projects for 1,400+ clients provides an extensive delivery pattern library across industries. |
| + | 2018 Global IT Leader recognition from Clutch, part of the Clutch 1000, is an independently sourced distinction. |
| + | 750+ engineers and consultants with dedicated MLOps and generative AI consulting roles, not just generalist developers relabeled. |
| - | AI is a comparatively newer addition to a company whose core 35-year identity is broader IT consulting. |
| - | 750-person total headcount spans many practice areas, so AI-specific bench depth is smaller than the total suggests. |
Who should choose Markovate?
Markovate is the right choice for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM)..
CEO brings direct enterprise AI leadership experience (AT&T, IBM) rather than a purely technical or agency background.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Retail & E-commerce, FinTech, Travel & Hospitality.
Who should choose ScienceSoft?
ScienceSoft is the right choice for enterprises wanting AI/MLOps delivery from a 35-year-old IT consultancy with an extensive multi-industry track record..
35+ years of continuous operating history (since 1989), among the longest-established vendors in this list.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Insurance, Manufacturing, Retail & E-commerce, Telecom.
Decision matrix: Markovate vs ScienceSoft
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Markovate |
| Your budget is at the lower end | Compare: Markovate (Not published) vs ScienceSoft (Not published) |
| You need specialist depth in a specific vertical | ScienceSoft |
| You need production MLOps support after model launch | ScienceSoft |
| You need consulting before committing to a build | ScienceSoft |
Use case fit: Markovate vs ScienceSoft
| Use case | Markovate fit | ScienceSoft fit | Winner |
|---|---|---|---|
| Company wants an AI agent or chatbot built by a team led by a former enterprise AI executive. | Strong | Strong | Both equally |
| Healthcare or fintech startup needs a scoped generative AI project from a small, focused vendor. | Strong | Strong | Both equally |
| Enterprise wants AI/MLOps delivery from a vendor with 35+ years of institutional stability. | Strong | Strong | Both equally |
| Insurance or healthcare company needs a vendor with a very large (4,200+) project delivery track record. | Limited | Strong | ScienceSoft |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: Markovate vs ScienceSoft
Markovate (4.1/5) is the stronger overall choice for most Machine Learning Development projects. CEO brings direct enterprise AI leadership experience (AT&T, IBM) rather than a purely technical or agency background.. It is best for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM)..
ScienceSoft (3.8/5) is the better choice when enterprises wanting AI/MLOps delivery from a 35-year-old IT consultancy with an extensive multi-industry track record.. If your situation matches those criteria, ScienceSoft is a competitive option.
Related comparisons
Markovate vs ScienceSoft FAQ
Is Markovate better than ScienceSoft?
Markovate (4.1/5) scores higher overall, but "better" depends on your use case. Markovate is better for companies wanting AI agent or chatbot development led by an executive with enterprise AI leadership background (AT&T, IBM).. ScienceSoft is better for enterprises wanting AI/MLOps delivery from a 35-year-old IT consultancy with an extensive multi-industry track record..
How do Markovate and ScienceSoft differ in pricing?
Markovate uses project-based, dedicated team pricing with a minimum engagement of Not published. ScienceSoft uses time & materials, managed engagement 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: Markovate or ScienceSoft?
Markovate 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 Markovate and ScienceSoft?
Markovate's primary differentiator is: ceo brings direct enterprise ai leadership experience (at&t, ibm) rather than a purely technical or agency background.. ScienceSoft's primary differentiator is: 35+ years of continuous operating history (since 1989), among the longest-established vendors in this list.. They also differ in team size (50–100 vs 750+), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Retail & E-commerce vs Healthcare, Insurance).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.