Addepto vs ScienceSoft: full comparison for 2026
Quick verdict
Addepto (4.3/5) edges ahead of ScienceSoft (4.0/5) overall. Addepto is the better choice for data teams needing warehouse work before an LLM project. ScienceSoft is the stronger option for healthcare and finance firms wanting one IT vendor. The right choice depends on your project size, budget, and required tech stack.
Addepto vs ScienceSoft: head-to-head summary
| Criterion | Addepto | ScienceSoft |
|---|---|---|
| Founded | 2018 | 1989 |
| HQ | Warsaw, Poland | McKinney, TX, USA |
| Team size | 50–249 | 750+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored | Long-established generalist covering both the surrounding software and the AI feature |
| Pricing model | $50–$99/hr (Clutch band); discovery workshops, then T&M | Fixed-price and T&M; rates on request |
| Min. engagement | $10,000+ (Clutch) | Not disclosed |
| Primary tech stack | Databricks, Snowflake, Azure OpenAI | Microsoft Dynamics 365, Salesforce, Azure OpenAI |
| Industries served | Manufacturing, Retail & e-commerce, Aviation, Financial services | Healthcare, Financial services, Retail, Manufacturing |
Addepto vs ScienceSoft: overview
Addepto
Addepto is a Warsaw-based AI and data consultancy that started trading in April 2018 (some directories list 2017). Clutch shows 50–249 employees, a $50–$99 hourly band and a $10,000 minimum project. CB Insights reports that KMS Technology acquired the company in December 2025, after an earlier tie-up with Grape Up. Its work typically begins with data engineering and moves on to generative AI, MLOps and AI discovery workshops.
ScienceSoft
ScienceSoft is an IT consulting and software development company founded in 1989, headquartered in McKinney, Texas, with more than 750 staff. It describes itself as an AI and software development firm, and its work spans healthcare IT, financial software, data analytics and machine learning integration. The company cites a 4.8 Clutch rating on its own pages. It is a generalist that covers AI as one service line among many.
Services and capabilities: Addepto vs ScienceSoft
| Capability | Addepto | ScienceSoft |
|---|---|---|
| CRM / ERP integration | ✗ | ✓ |
| LLM API gateway & cost control | ✓ | ✗ |
| Document processing | ✗ | ✓ |
| Agentic workflows | ✗ | ✗ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✗ | ✗ |
| PII masking & access control | ✗ | ✗ |
Tech stack comparison: Addepto vs ScienceSoft
| Framework / platform | Addepto | ScienceSoft |
|---|---|---|
| Salesforce | N/A | ✓ |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | N/A | ✓ |
| HubSpot | N/A | N/A |
| Snowflake | ✓ | N/A |
| Databricks | ✓ | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | N/A | N/A |
| LangChain | ✓ | N/A |
| ServiceNow | N/A | N/A |
Pricing comparison: Addepto vs ScienceSoft
| Criterion | Addepto | ScienceSoft |
|---|---|---|
| Minimum engagement | $10,000+ (Clutch) | Not disclosed |
| Engagement models | Fixed project, Time & materials | Fixed project, Time & materials, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Addepto vs ScienceSoft
| Dimension | Addepto | ScienceSoft |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail & e-commerce, Aviation | Healthcare, Financial services, Retail |
| Best use cases | Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant., Productionizing ML models with MLflow and monitoring. | Adding AI document intake to a healthcare application., Analytics dashboards with predictive models for a lender. |
| Typical project type | Fixed project | Fixed project |
Addepto vs ScienceSoft: pros and cons
| Addepto | |
|---|---|
| + | Publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward |
| + | Databricks and Spark experience helps when the data estate is the real blocker |
| + | Discovery workshops scope use cases before larger spend |
| + | Predictive analytics and LLM work available from the same team |
| - | Acquired by KMS Technology in December 2025 (per CB Insights), so ownership and leadership may change |
| - | Corporate history includes several restructurings, which complicates long-term vendor planning |
| - | Limited published work inside CRM platforms |
| ScienceSoft | |
|---|---|
| + | Three decades of operation suggests stability |
| + | Healthcare and finance domain knowledge |
| + | Can cover integration, testing and support under one contract |
| - | AI is one practice among many, with less specialist depth |
| - | Content-heavy marketing makes independent comparison harder |
Who should choose Addepto?
A typical fit: building a Databricks lakehouse that later feeds demand forecasts and an internal assistant.
Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Manufacturing, Retail & e-commerce, Aviation, Financial services.
Who should choose ScienceSoft?
A typical fit: adding AI document intake to a healthcare application.
Long-established generalist covering both the surrounding software and the AI feature. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Retail, Manufacturing.
Decision matrix: Addepto vs ScienceSoft
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Neither advertises one; ask for a scoped pilot |
| AI has to work inside your existing CRM or ERP | ScienceSoft |
| Personal data must be masked and answers limited by user permissions | Ask both for their PII and access-control design |
| Your budget is at the lower end | Compare: Addepto ($10,000+ (Clutch)) vs ScienceSoft (Not disclosed) |
| You want the vendor to run the AI service after launch | Neither offers managed services; plan in-house operations |
| You are building multi-step agents across systems | Neither lists agentic AI work |
Use case fit: Addepto vs ScienceSoft
| Use case | Addepto fit | ScienceSoft fit | Winner |
|---|---|---|---|
| Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant. | Strong | Limited | Addepto |
| Productionizing ML models with MLflow and monitoring. | Strong | Limited | Addepto |
| Adding AI document intake to a healthcare application. | Limited | Strong | ScienceSoft |
| Analytics dashboards with predictive models for a lender. | Limited | Strong | ScienceSoft |
Verdict: Addepto vs ScienceSoft
Addepto (4.3/5) is the stronger overall choice for most AI Integration projects. Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored.
ScienceSoft (4.0/5) is worth a look if you need analytics dashboards with predictive models for a lender. If your situation matches that, ScienceSoft is a competitive option.
Related comparisons
Addepto vs ScienceSoft FAQ
Is Addepto better than ScienceSoft?
Addepto (4.3/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward. ScienceSoft's strongest advantage: three decades of operation suggests stability.
How do Addepto and ScienceSoft differ in pricing?
Addepto pricing: $50–$99/hr (Clutch band); discovery workshops, then T&M. Minimum engagement: $10,000+ (Clutch). ScienceSoft pricing: Fixed-price and T&M; rates on request. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or ScienceSoft?
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 ScienceSoft?
Addepto's primary differentiator is: data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. ScienceSoft's primary differentiator is: long-established generalist covering both the surrounding software and the AI feature. They also differ in team size (50–249 vs 750+), minimum engagement ($10,000+ (Clutch) vs Not disclosed), and primary industries served (Manufacturing, Retail & e-commerce vs Healthcare, Financial services).
Verify all details directly with each company before making a decision.