deepsense.ai vs Addepto: full comparison for 2026
Quick verdict
deepsense.ai (4.4/5) edges ahead of Addepto (4.3/5) overall. deepsense.ai is the better choice for engineering teams wanting a strong RAG partner. Addepto is the stronger option for data teams needing warehouse work before an LLM project. The right choice depends on your project size, budget, and required tech stack.
deepsense.ai vs Addepto: head-to-head summary
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Founded | 2014 | 2018 |
| HQ | Warsaw, Poland | Warsaw, Poland |
| Team size | 101–200 | 50–249 |
| Rating | 4.4 / 5 | 4.3 / 5 |
| Primary differentiator | Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets | Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored |
| Pricing model | T&M and dedicated teams; rates on request | $50–$99/hr (Clutch band); discovery workshops, then T&M |
| Min. engagement | Not disclosed | $10,000+ (Clutch) |
| Primary tech stack | LangChain, Azure OpenAI, AWS Bedrock | Databricks, Snowflake, Azure OpenAI |
| Industries served | Manufacturing, Retail, Financial services, Healthcare | Manufacturing, Retail & e-commerce, Aviation, Financial services |
deepsense.ai vs Addepto: overview
deepsense.ai
deepsense.ai is an AI-first engineering company founded in 2014 out of the AI division of CodiLime, with headquarters in Warsaw and an office in Palo Alto. It employs roughly 120–200 people, including several Kaggle competition winners. Its integration work centres on LLM applications using retrieval-augmented generation (RAG), plus computer vision and edge deployments for manufacturing. It lists technical partnerships with OpenAI, NVIDIA, Anyscale and LangChain.
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.
Services and capabilities: deepsense.ai vs Addepto
| Capability | deepsense.ai | Addepto |
|---|---|---|
| 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: deepsense.ai vs Addepto
| Framework / platform | deepsense.ai | Addepto |
|---|---|---|
| Salesforce | N/A | N/A |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | N/A | N/A |
| HubSpot | N/A | N/A |
| Snowflake | N/A | ✓ |
| Databricks | N/A | ✓ |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | N/A |
| LangChain | ✓ | ✓ |
| ServiceNow | N/A | N/A |
Pricing comparison: deepsense.ai vs Addepto
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Minimum engagement | Not disclosed | $10,000+ (Clutch) |
| Engagement models | Time & materials, Dedicated team | Fixed project, Time & materials |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Accessible |
Target audience comparison: deepsense.ai vs Addepto
| Dimension | deepsense.ai | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail, Financial services | Manufacturing, Retail & e-commerce, Aviation |
| Best use cases | Retrieval assistants over technical manuals or internal knowledge bases., Visual defect detection on production lines with edge inference. | Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant., Productionizing ML models with MLflow and monitoring. |
| Typical project type | Time & materials | Fixed project |
deepsense.ai vs Addepto: pros and cons
| deepsense.ai | |
|---|---|
| + | Deep ML talent, with evaluation of retrieval quality treated as part of the build |
| + | Experience deploying models on edge hardware as well as in the cloud |
| + | Open publication record and active LangChain contribution history |
| + | Comfortable working alongside an in-house data team |
| - | Less experience embedding AI inside packaged CRM or ERP products |
| - | Engagements lean toward engineering capacity, with less change-management support |
| 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 |
Who should choose deepsense.ai?
A typical fit: retrieval assistants over technical manuals or internal knowledge bases.
Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail, Financial services, Healthcare.
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.
Decision matrix: deepsense.ai vs Addepto
| 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 | Neither lists CRM/ERP integration work |
| 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: deepsense.ai (Not disclosed) vs Addepto ($10,000+ (Clutch)) |
| 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 | deepsense.ai |
Use case fit: deepsense.ai vs Addepto
| Use case | deepsense.ai fit | Addepto fit | Winner |
|---|---|---|---|
| Retrieval assistants over technical manuals or internal knowledge bases. | Strong | Limited | deepsense.ai |
| Visual defect detection on production lines with edge inference. | Strong | Limited | deepsense.ai |
| Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant. | Limited | Strong | Addepto |
| Productionizing ML models with MLflow and monitoring. | Limited | Strong | Addepto |
Verdict: deepsense.ai vs Addepto
deepsense.ai (4.4/5) is the stronger overall choice for most AI Integration projects. Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets.
Addepto (4.3/5) is worth a look if you need productionizing ML models with MLflow and monitoring. If your situation matches that, Addepto is a competitive option.
Related comparisons
deepsense.ai vs Addepto FAQ
Is deepsense.ai better than Addepto?
deepsense.ai (4.4/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: deep ML talent, with evaluation of retrieval quality treated as part of the build. Addepto's strongest advantage: publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward.
How do deepsense.ai and Addepto differ in pricing?
deepsense.ai pricing: T&M and dedicated teams; rates on request. Addepto pricing: $50–$99/hr (Clutch band); discovery workshops, then T&M. Minimum engagement: $10,000+ (Clutch). Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: deepsense.ai or Addepto?
deepsense.ai 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 deepsense.ai and Addepto?
deepsense.ai's primary differentiator is: research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. Addepto's primary differentiator is: data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. They also differ in team size (101–200 vs 50–249), minimum engagement (Not disclosed vs $10,000+ (Clutch)), and primary industries served (Manufacturing, Retail vs Manufacturing, Retail & e-commerce).
Verify all details directly with each company before making a decision.