deepsense.ai vs Thoughtworks: full comparison for 2026
Quick verdict
deepsense.ai (4.4/5) edges ahead of Thoughtworks (4.1/5) overall. deepsense.ai is the better choice for engineering teams wanting a strong RAG partner. Thoughtworks is the stronger option for engineering-led firms that value delivery practice. The right choice depends on your project size, budget, and required tech stack.
deepsense.ai vs Thoughtworks: head-to-head summary
| Criterion | deepsense.ai | Thoughtworks |
|---|---|---|
| Founded | 2014 | 1993 |
| HQ | Warsaw, Poland | Chicago, IL, USA |
| Team size | 101–200 | 10,000+ |
| Rating | 4.4 / 5 | 4.1 / 5 |
| Primary differentiator | Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets | Long-standing engineering discipline, testing and continuous delivery applied to AI features |
| Pricing model | T&M and dedicated teams; rates on request | T&M with senior-weighted teams; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | LangChain, Azure OpenAI, AWS Bedrock | Azure OpenAI, AWS Bedrock, Google Vertex AI |
| Industries served | Manufacturing, Retail, Financial services, Healthcare | Financial services, Retail, Public sector, Healthcare |
deepsense.ai vs Thoughtworks: 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.
Thoughtworks
Thoughtworks is a software engineering consultancy founded in 1993 and headquartered in Chicago, with about 10,000 people across 18 countries. Apax Partners took it private in a deal of about $1.75 billion that completed in November 2024, after a restructuring that cut 6–7% of staff. It now markets AI-first software delivery, and in March 2026 it formed an AI-focused joint venture with consulting firm Teneo. Its reputation rests on engineering practice more than on packaged integrations.
Services and capabilities: deepsense.ai vs Thoughtworks
| Capability | deepsense.ai | Thoughtworks |
|---|---|---|
| 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 Thoughtworks
| Framework / platform | deepsense.ai | Thoughtworks |
|---|---|---|
| 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 | ✓ |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | ✓ | ✓ |
| LangChain | ✓ | N/A |
| ServiceNow | N/A | N/A |
Pricing comparison: deepsense.ai vs Thoughtworks
| Criterion | deepsense.ai | Thoughtworks |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Time & materials, Dedicated team | Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: deepsense.ai vs Thoughtworks
| Dimension | deepsense.ai | Thoughtworks |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Manufacturing, Retail, Financial services | Financial services, Retail, Public sector |
| Best use cases | Retrieval assistants over technical manuals or internal knowledge bases., Visual defect detection on production lines with edge inference. | Modernizing a legacy application and adding AI features in the same programme., Setting up evaluation and release practices for LLM features. |
| Typical project type | Time & materials | Time & materials |
deepsense.ai vs Thoughtworks: 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 |
| Thoughtworks | |
|---|---|
| + | Strong testing and continuous-delivery culture carries over to model and prompt changes |
| + | Publishes its Technology Radar, which offers a transparent view of its technical opinions |
| + | Comfortable modernizing legacy systems alongside the AI work |
| - | Taken private by Apax Partners in 2024 after cost-cutting, so the account team may change |
| - | Few packaged integrations for CRM or ERP suites |
| - | Senior-heavy teams carry higher blended rates |
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 Thoughtworks?
A typical fit: modernizing a legacy application and adding AI features in the same programme.
Long-standing engineering discipline, testing and continuous delivery applied to AI features. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Retail, Public sector, Healthcare.
Decision matrix: deepsense.ai vs Thoughtworks
| 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 Thoughtworks (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 | deepsense.ai |
Use case fit: deepsense.ai vs Thoughtworks
| Use case | deepsense.ai fit | Thoughtworks 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 |
| Modernizing a legacy application and adding AI features in the same programme. | Limited | Strong | Thoughtworks |
| Setting up evaluation and release practices for LLM features. | Limited | Strong | Thoughtworks |
Verdict: deepsense.ai vs Thoughtworks
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.
Thoughtworks (4.1/5) is worth a look if you need setting up evaluation and release practices for LLM features. If your situation matches that, Thoughtworks is a competitive option.
Related comparisons
deepsense.ai vs Thoughtworks FAQ
Is deepsense.ai better than Thoughtworks?
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. Thoughtworks's strongest advantage: strong testing and continuous-delivery culture carries over to model and prompt changes.
How do deepsense.ai and Thoughtworks differ in pricing?
deepsense.ai pricing: T&M and dedicated teams; rates on request. Thoughtworks pricing: T&M with senior-weighted teams; 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 Thoughtworks?
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 Thoughtworks?
deepsense.ai's primary differentiator is: research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. Thoughtworks's primary differentiator is: long-standing engineering discipline, testing and continuous delivery applied to AI features. They also differ in team size (101–200 vs 10,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Manufacturing, Retail vs Financial services, Retail).
Verify all details directly with each company before making a decision.