Addepto vs Neurons Lab: full comparison for 2026
Quick verdict
Addepto (3.9/5) edges ahead of Neurons Lab (3.9/5) overall. Addepto is the better choice for industrial and automotive companies adding AI and data engineers to an internal team. Neurons Lab is the stronger option for banks and insurers that need agentic AI engineers who know financial-services constraints. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Neurons Lab: head-to-head summary
| Criterion | Addepto | Neurons Lab |
|---|---|---|
| Founded | 2017 | 2019 |
| HQ | Warsaw, Poland | London, UK |
| Team size | 50–99 (directory estimate) | 50–100 staff; 500+ network engineers (per company) |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | AI-heavy team with manufacturing domain experience, now backed by a larger group | Financial-services AI with AWS GenAI competency and forward-deployed engineers |
| Pricing model | Collaborative team model or managed delivery; rates on request | Project or continuous-delivery retainer; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Databricks, Spark | Python, Amazon Bedrock, AWS SageMaker |
| Industries served | Manufacturing, Automotive, Retail, Aviation | Banking, Insurance, Financial services, Public sector |
Addepto vs Neurons Lab: overview
Addepto
Addepto has worked on AI and data in Warsaw since 2017, with a strong client base in industrial and automotive companies. KMS Technology, an Atlanta engineering firm backed by Sunstone Partners, acquired it in December 2025. Its collaborative cooperation model puts Addepto engineers alongside the client's own team, and the company has said publicly it is not a body-leasing firm. After the deal, its CEO said 97% of the team are AI engineers.
Neurons Lab
Neurons Lab was registered in London in October 2019 and now focuses on agentic AI for mid-to-large banks, financial services firms and insurers. Clients named in its case studies include HSBC, Visa and AXA. Its continuous delivery service puts forward-deployed engineers alongside the client's team, drawing on a distributed network of 500+ engineers, though staff headcount is closer to 50–100. It holds AWS Advanced Partner status with the generative AI competency and a second office in Singapore.
Services and capabilities: Addepto vs Neurons Lab
| Capability | Addepto | Neurons Lab |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| AI agent development | ✗ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Data engineering | ✓ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Forward-deployed engineers | ✗ | ✓ |
| Access to a wider AI talent network | ✗ | ✓ |
Tech stack comparison: Addepto vs Neurons Lab
| Framework / platform | Addepto | Neurons Lab |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
Pricing comparison: Addepto vs Neurons Lab
| Criterion | Addepto | Neurons Lab |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Embedded team, Project delivery | Embedded team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Addepto vs Neurons Lab
| Dimension | Addepto | Neurons Lab |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Automotive, Retail | Banking, Insurance, Financial services |
| Best use cases | Adding Databricks engineers to a manufacturer's data team, Building a GenAI assistant for automotive service documents | Building agentic workflows for a bank's operations team, Embedding engineers to keep insurer AI systems up to date |
| Typical project type | Embedded team | Embedded team |
Addepto vs Neurons Lab: pros and cons
| Addepto | |
|---|---|
| + | Nearly the whole team is AI engineers, according to its CEO |
| + | Industrial and automotive client experience |
| + | KMS ownership adds broader engineering capacity behind it |
| - | Acquired by KMS Technology in December 2025; ownership changes can bring new contract terms |
| - | Prefers joint delivery to straight staff placement |
| - | Team size estimates range from 8 to 99 |
| Neurons Lab | |
|---|---|
| + | Named clients in banking and payments |
| + | AWS Advanced Partner with GenAI competency and public-sector partner status |
| + | Singapore office helps with Asia-Pacific coverage |
| - | No standalone staff-augmentation service; engineers are deployed as part of its delivery work |
| - | Headcount figures mix staff with a much larger external network |
| - | Sector focus makes it a poor fit outside financial services |
Who should choose Addepto?
A typical fit: adding Databricks engineers to a manufacturer's data team.
AI-heavy team with manufacturing domain experience, now backed by a larger group. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Automotive, Retail, Aviation.
Who should choose Neurons Lab?
A typical fit: building agentic workflows for a bank's operations team.
Financial-services AI with AWS GenAI competency and forward-deployed engineers. Minimum engagement is not publicly disclosed. Works best with clients in Banking, Insurance, Financial services, Public sector.
Decision matrix: Addepto vs Neurons Lab
| Your situation | Recommended choice |
|---|---|
| You need one AI specialist part-time | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Addepto |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| Your budget is at the lower end | Compare: Addepto (Not published) vs Neurons Lab (Not published) |
| You need engineers deployed inside your organization | Both; Addepto rates higher overall |
| You need specialist depth in a specific vertical | Addepto |
Use case fit: Addepto vs Neurons Lab
| Use case | Addepto fit | Neurons Lab fit | Winner |
|---|---|---|---|
| Adding Databricks engineers to a manufacturer's data team | Strong | Limited | Addepto |
| Building a GenAI assistant for automotive service documents | Strong | Strong | Both equally |
| Building agentic workflows for a bank's operations team | Strong | Strong | Both equally |
| Embedding engineers to keep insurer AI systems up to date | Limited | Strong | Neurons Lab |
Verdict: Addepto vs Neurons Lab
Addepto (3.9/5) is the stronger overall choice for most AI-Native Staff Augmentation projects. AI-heavy team with manufacturing domain experience, now backed by a larger group.
Neurons Lab (3.9/5) is worth a look if you need embedding engineers to keep insurer AI systems up to date. If your situation matches that, Neurons Lab is a competitive option.
Related comparisons
Addepto vs Neurons Lab FAQ
Is Addepto better than Neurons Lab?
Addepto (3.9/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: nearly the whole team is AI engineers, according to its CEO. Neurons Lab's strongest advantage: named clients in banking and payments.
How do Addepto and Neurons Lab differ in pricing?
Addepto uses collaborative team model or managed delivery; rates on request pricing. Neurons Lab uses project or continuous-delivery retainer; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or Neurons Lab?
Neurons Lab 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 Addepto and Neurons Lab?
Addepto's primary differentiator is: AI-heavy team with manufacturing domain experience, now backed by a larger group. Neurons Lab's primary differentiator is: financial-services AI with AWS GenAI competency and forward-deployed engineers. They also differ in team size (50–99 (directory estimate) vs 50–100 staff; 500+ network engineers (per company)), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Automotive vs Banking, Insurance).
Verify all details directly with each company before making a decision.