deepsense.ai vs Addepto: full comparison for 2026
Quick verdict
deepsense.ai (4.5/5) edges ahead of Addepto (4.2/5) overall. deepsense.ai is the better choice for teams that need measured accuracy before launch. Addepto is the stronger option for mid-size firms wanting tested LLM apps cheaply. The right choice depends on how far your pilot has got, your budget, and who will run the system after launch.
deepsense.ai vs Addepto: head-to-head summary
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Founded | 2014 | 2017 |
| HQ | Warsaw, Poland | Warsaw, Poland |
| Team size | 120+ | 50–249 |
| Rating | 4.5 / 5 | 4.2 / 5 |
| Primary differentiator | Evaluation-first engineering that proves accuracy on your data before release | Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point |
| Pricing model | Project-based; $100–$149/hr (Clutch band) | Project-based; $50–$99/hr (Clutch band) |
| Min. engagement | $25,000+ (Clutch) | $10,000+ (Clutch) |
| Primary tech stack | Python, PyTorch, LangChain | Databricks, Azure, AWS |
| Industries served | Retail, Manufacturing, Financial services, Healthcare, Media | Manufacturing, Aviation, Logistics, Retail, Financial services |
deepsense.ai vs Addepto: overview
deepsense.ai
Founded in Warsaw in 2014, deepsense.ai has about 120 AI specialists and an office in Palo Alto. Its work covers language models, retrieval search, and computer vision, and its teams build the evaluation sets that tell you whether a system is accurate enough to release. That evaluation habit is the reason it ranks high here. Clutch lists $100–$149 an hour and a $25,000+ minimum project, which is expensive for a Polish firm.
Addepto
Addepto was founded in Warsaw in 2017 and was acquired in December 2025 by KMS Technology, an Atlanta engineering company backed by Sunstone Partners. It built ContextCheck, an open-source framework for testing language models and chatbots, which says something about how it approaches quality before release. Its chief executive says 97% of staff are AI engineers (per company website; independently unverifiable). Clutch lists $50–$99 an hour and a $10,000+ minimum project.
Services and capabilities: deepsense.ai vs Addepto
| Capability | deepsense.ai | Addepto |
|---|---|---|
| LLM gateway & model routing | ✗ | ✗ |
| Regression tests on prompt and model changes | ✓ | ✓ |
| Canary or staged rollout | ✗ | ✗ |
| Hallucination and drift monitoring | ✗ | ✗ |
| MLOps & model serving | ✓ | ✓ |
| Fixed-scope pilot | ✗ | ✗ |
| Managed run after launch | ✗ | ✗ |
Tech stack comparison: deepsense.ai vs Addepto
| Framework / platform | deepsense.ai | Addepto |
|---|---|---|
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Kubernetes | N/A | N/A |
| MLflow | N/A | N/A |
| Databricks | N/A | ✓ |
| Amazon Bedrock | N/A | N/A |
| Vertex AI | N/A | N/A |
| LangChain | ✓ | ✓ |
| Snowflake | N/A | N/A |
Pricing comparison: deepsense.ai vs Addepto
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Minimum engagement | $25,000+ (Clutch) | $10,000+ (Clutch) |
| Engagement models | Fixed-scope project, Time & materials, Dedicated team | Fixed-scope project, Time & materials, Dedicated team |
| Rate transparency | Minimum disclosed | 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 | Retail, Manufacturing, Financial services | Manufacturing, Aviation, Logistics |
| Best use cases | Retrieval search over internal documents with measured accuracy., Evaluating a vendor's AI before rolling it out. | Testing a chatbot or LLM app before release., AI on manufacturing and aviation data. |
| Typical project type | Fixed-scope project | Fixed-scope project |
deepsense.ai vs Addepto: pros and cons
| deepsense.ai | |
|---|---|
| + | Builds evaluation sets on real data before deciding a system is ready |
| + | Research-grade depth in language models and computer vision |
| + | Retrieval search projects come with measured answer accuracy |
| + | Senior engineers stay involved after the first release |
| - | Higher Clutch rate band than most Central European peers |
| - | Smaller team than the global engineering firms |
| - | No managed-run service listed after launch |
| Addepto | |
|---|---|
| + | ContextCheck shows real investment in testing language models |
| + | A $10,000+ Clutch minimum makes a small first project possible |
| + | Databricks experience for data-heavy builds |
| + | Team is almost all engineers |
| - | Acquired by KMS Technology in December 2025, so teams and priorities may change |
| - | No managed-run service listed |
| - | Less depth on staged rollouts than the leaders |
Who should choose deepsense.ai?
A typical fit: retrieval search over internal documents with measured accuracy.
Evaluation-first engineering that proves accuracy on your data before release. Minimum engagement starts at $25,000+ (Clutch). Works best with clients in Retail, Manufacturing, Financial services, Healthcare, Media.
Who should choose Addepto?
A typical fit: testing a chatbot or LLM app before release.
Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Manufacturing, Aviation, Logistics, Retail, Financial services.
Decision matrix: deepsense.ai vs Addepto
| Your situation | Recommended choice |
|---|---|
| Your pilot works but nobody trusts it in production yet | Ask each for its release and rollback process |
| Model API spend is growing faster than usage | Neither lists a gateway; ask how cost per feature is tracked |
| You need someone to watch quality after launch | Neither; plan for your own team to monitor it |
| You run classic ML models that need serving and retraining | Both cover MLOps |
| You want a priced pilot before a full rollout | Neither advertises one; ask for a scoped quote |
| Your budget is at the lower end | Addepto |
| You need a large team for many products at once | deepsense.ai |
Use case fit: deepsense.ai vs Addepto
| Use case | deepsense.ai fit | Addepto fit | Winner |
|---|---|---|---|
| Retrieval search over internal documents with measured accuracy. | Strong | Limited | deepsense.ai |
| Evaluating a vendor's AI before rolling it out. | Strong | Limited | deepsense.ai |
| Testing a chatbot or LLM app before release. | Limited | Strong | Addepto |
| AI on manufacturing and aviation data. | Limited | Strong | Addepto |
Verdict: deepsense.ai vs Addepto
deepsense.ai (4.5/5) is the stronger overall choice for most AI Implementation projects. Evaluation-first engineering that proves accuracy on your data before release.
Addepto (4.2/5) is worth a look if you need AI on manufacturing and aviation data. 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 (4.5/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: builds evaluation sets on real data before deciding a system is ready. Addepto's strongest advantage: ContextCheck shows real investment in testing language models.
How do deepsense.ai and Addepto differ in pricing?
deepsense.ai's pricing: project-based; $100–$149/hr (Clutch band) with a minimum engagement of $25,000+ (Clutch). Addepto's pricing: project-based; $50–$99/hr (Clutch band) with a minimum engagement of $10,000+ (Clutch). Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
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 provider before shortlisting.
What are the main differences between deepsense.ai and Addepto?
deepsense.ai's primary differentiator is: evaluation-first engineering that proves accuracy on your data before release. Addepto's primary differentiator is: open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point. They also differ in team size (120+ vs 50–249), minimum engagement ($25,000+ (Clutch) vs $10,000+ (Clutch)), and primary industries served (Retail, Manufacturing vs Manufacturing, Aviation).
Verify all details directly with each provider before making a decision.