Neurons Lab vs deepsense.ai: full comparison for 2026
Quick verdict
Neurons Lab (4.5/5) edges ahead of deepsense.ai (4.4/5) overall. Neurons Lab is the better choice for banks and insurers piloting agentic AI under regulation. deepsense.ai is the stronger option for engineering teams wanting a strong RAG partner. The right choice depends on your project size, budget, and required tech stack.
Neurons Lab vs deepsense.ai: head-to-head summary
| Criterion | Neurons Lab | deepsense.ai |
|---|---|---|
| Founded | 2019 | 2014 |
| HQ | London, UK | Warsaw, Poland |
| Team size | 51–200 | 101–200 |
| Rating | 4.5 / 5 | 4.4 / 5 |
| Primary differentiator | Financial-services agent work delivered by an AWS Advanced Tier partner that also holds a public-sector designation | Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets |
| Pricing model | Fixed-price discovery and proof of concept, then T&M; rates on request | T&M and dedicated teams; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | AWS Bedrock, Amazon SageMaker, LangChain | LangChain, Azure OpenAI, AWS Bedrock |
| Industries served | Financial services, Insurance, Healthcare, Public sector | Manufacturing, Retail, Financial services, Healthcare |
Neurons Lab vs deepsense.ai: overview
Neurons Lab
Neurons Lab is an AI-first consultancy incorporated in London in October 2019, with a second office in Singapore and a distributed engineering team. It is an AWS Advanced Tier Services Partner with the Generative AI competency and joined the AWS Public Sector Partner programme in September 2024. Recent published work leans toward financial services, including an AI-driven investment product built with a global asset manager. Third-party estimates put direct headcount at roughly 50–200, supplemented by a contractor network.
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.
Services and capabilities: Neurons Lab vs deepsense.ai
| Capability | Neurons Lab | deepsense.ai |
|---|---|---|
| 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: Neurons Lab vs deepsense.ai
| Framework / platform | Neurons Lab | deepsense.ai |
|---|---|---|
| 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 | N/A | ✓ |
| AWS Bedrock | ✓ | ✓ |
| LangChain | ✓ | ✓ |
| ServiceNow | N/A | N/A |
Pricing comparison: Neurons Lab vs deepsense.ai
| Criterion | Neurons Lab | deepsense.ai |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope audit or pilot, Time & materials | Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Neurons Lab vs deepsense.ai
| Dimension | Neurons Lab | deepsense.ai |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Insurance, Healthcare | Manufacturing, Retail, Financial services |
| Best use cases | Research or advisory agents for an asset manager that pull from internal and market data., Customer-service agents for an insurer with audit logging on every action. | Retrieval assistants over technical manuals or internal knowledge bases., Visual defect detection on production lines with edge inference. |
| Typical project type | Fixed-scope audit or pilot | Time & materials |
Neurons Lab vs deepsense.ai: pros and cons
| Neurons Lab | |
|---|---|
| + | Regulated-finance experience shows up in how it scopes data access and model risk |
| + | Fixed-price discovery and proof-of-concept stages limit early spend |
| + | AWS Advanced Tier and GenAI competency are confirmed through AWS programmes |
| + | Small senior teams with direct access to founders |
| - | Not yet AWS Premier Tier, and its own job ads have described that as a future goal |
| - | Weaker fit for Azure- or SAP-heavy estates |
| - | A small core team relies on a contractor network for larger programmes |
| 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 |
Who should choose Neurons Lab?
A typical fit: research or advisory agents for an asset manager that pull from internal and market data.
Financial-services agent work delivered by an AWS Advanced Tier partner that also holds a public-sector designation. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Insurance, Healthcare, Public sector.
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.
Decision matrix: Neurons Lab vs deepsense.ai
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Neurons Lab |
| 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 | Neurons Lab |
| Your budget is at the lower end | Compare: Neurons Lab (Not disclosed) vs deepsense.ai (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: Neurons Lab vs deepsense.ai
| Use case | Neurons Lab fit | deepsense.ai fit | Winner |
|---|---|---|---|
| Research or advisory agents for an asset manager that pull from internal and market data. | Strong | Limited | Neurons Lab |
| Customer-service agents for an insurer with audit logging on every action. | Strong | Limited | Neurons Lab |
| Retrieval assistants over technical manuals or internal knowledge bases. | Limited | Strong | deepsense.ai |
| Visual defect detection on production lines with edge inference. | Limited | Strong | deepsense.ai |
Verdict: Neurons Lab vs deepsense.ai
Neurons Lab (4.5/5) is the stronger overall choice for most AI Integration projects. Financial-services agent work delivered by an AWS Advanced Tier partner that also holds a public-sector designation.
deepsense.ai (4.4/5) is worth a look if you need visual defect detection on production lines with edge inference. If your situation matches that, deepsense.ai is a competitive option.
Related comparisons
Neurons Lab vs deepsense.ai FAQ
Is Neurons Lab better than deepsense.ai?
Neurons Lab (4.5/5) scores higher overall, but "better" depends on your use case. Neurons Lab's strongest advantage: regulated-finance experience shows up in how it scopes data access and model risk. deepsense.ai's strongest advantage: deep ML talent, with evaluation of retrieval quality treated as part of the build.
How do Neurons Lab and deepsense.ai differ in pricing?
Neurons Lab pricing: Fixed-price discovery and proof of concept, then T&M; rates on request. deepsense.ai pricing: T&M and dedicated 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: Neurons Lab or deepsense.ai?
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 Neurons Lab and deepsense.ai?
Neurons Lab's primary differentiator is: financial-services agent work delivered by an AWS Advanced Tier partner that also holds a public-sector designation. deepsense.ai's primary differentiator is: research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. They also differ in team size (51–200 vs 101–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Insurance vs Manufacturing, Retail).
Verify all details directly with each company before making a decision.