deepsense.ai vs Markovate: full comparison for 2026
Quick verdict
deepsense.ai (4.4/5) edges ahead of Markovate (3.9/5) overall. deepsense.ai is the better choice for engineering teams wanting a strong RAG partner. Markovate is the stronger option for startups wanting a quick generative AI build. The right choice depends on your project size, budget, and required tech stack.
deepsense.ai vs Markovate: head-to-head summary
| Criterion | deepsense.ai | Markovate |
|---|---|---|
| Founded | 2014 | 2015 |
| HQ | Warsaw, Poland | San Francisco, CA, USA |
| Team size | 101–200 | 50–200 |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Primary differentiator | Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets | Generative AI app builds for startups with a fast proof-of-concept focus |
| Pricing model | T&M and dedicated teams; rates on request | Fixed-price and T&M; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | LangChain, Azure OpenAI, AWS Bedrock | Azure OpenAI, AWS Bedrock, LangChain |
| Industries served | Manufacturing, Retail, Financial services, Healthcare | SaaS, Healthcare, Retail & e-commerce, Logistics |
deepsense.ai vs Markovate: 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.
Markovate
Markovate is an AI development agency founded in 2015, headquartered in San Francisco with a presence in Toronto. Directory headcount estimates sit between about 50 and 200. It builds generative AI apps, agents and integrations for startups and mid-size firms. It publishes a large volume of marketing content, while independent detail on production integrations is limited.
Services and capabilities: deepsense.ai vs Markovate
| Capability | deepsense.ai | Markovate |
|---|---|---|
| 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 Markovate
| Framework / platform | deepsense.ai | Markovate |
|---|---|---|
| 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 | N/A |
| Databricks | N/A | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | ✓ |
| LangChain | ✓ | ✓ |
| ServiceNow | N/A | N/A |
Pricing comparison: deepsense.ai vs Markovate
| Criterion | deepsense.ai | Markovate |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Time & materials, Dedicated team | Fixed project, Time & materials |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: deepsense.ai vs Markovate
| Dimension | deepsense.ai | Markovate |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail, Financial services | SaaS, Healthcare, Retail & e-commerce |
| Best use cases | Retrieval assistants over technical manuals or internal knowledge bases., Visual defect detection on production lines with edge inference. | A generative AI MVP for a startup., Chat interfaces over product documentation. |
| Typical project type | Time & materials | Fixed project |
deepsense.ai vs Markovate: 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 |
| Markovate | |
|---|---|
| + | Quick turnaround on generative AI prototypes |
| + | Good fit for startups without an in-house AI team |
| + | Experience with chat and agent interfaces |
| - | Thin independent evidence of enterprise CRM or ERP integration |
| - | Headcount estimates vary widely between directories |
| - | Ratings and awards mostly cited from its own materials |
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 Markovate?
A typical fit: a generative AI MVP for a startup.
Generative AI app builds for startups with a fast proof-of-concept focus. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Healthcare, Retail & e-commerce, Logistics.
Decision matrix: deepsense.ai vs Markovate
| 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 Markovate (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 | Both |
Use case fit: deepsense.ai vs Markovate
| Use case | deepsense.ai fit | Markovate 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 |
| A generative AI MVP for a startup. | Strong | Strong | Both equally |
| Chat interfaces over product documentation. | Limited | Strong | Markovate |
Verdict: deepsense.ai vs Markovate
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.
Markovate (3.9/5) is worth a look if you need chat interfaces over product documentation. If your situation matches that, Markovate is a competitive option.
Related comparisons
deepsense.ai vs Markovate FAQ
Is deepsense.ai better than Markovate?
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. Markovate's strongest advantage: quick turnaround on generative AI prototypes.
How do deepsense.ai and Markovate differ in pricing?
deepsense.ai pricing: T&M and dedicated teams; rates on request. Markovate 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: deepsense.ai or Markovate?
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 Markovate?
deepsense.ai's primary differentiator is: research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. Markovate's primary differentiator is: generative AI app builds for startups with a fast proof-of-concept focus. They also differ in team size (101–200 vs 50–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Manufacturing, Retail vs SaaS, Healthcare).
Verify all details directly with each company before making a decision.