deepsense.ai vs Harnham: full comparison for 2026
Quick verdict
deepsense.ai (4.6/5) edges ahead of Harnham (3.7/5) overall. deepsense.ai is the better choice for teams that need a senior ML researcher who can also put models into production. Harnham is the stronger option for companies hiring permanent data or ML staff in the UK or U.S. through a specialist agency. The right choice depends on your project size, budget, and required tech stack.
deepsense.ai vs Harnham: head-to-head summary
| Criterion | deepsense.ai | Harnham |
|---|---|---|
| Founded | 2014 | 2006 |
| HQ | Warsaw, Poland | London, United Kingdom |
| Team size | 100–200 | 100–500 |
| Rating | 4.6 / 5 | 3.7 / 5 |
| Primary differentiator | A research-heavy bench of about 120 employed AI specialists with ten years of production work | Twenty years of recruiting only in data and analytics |
| Pricing model | Team extension billed monthly per engineer; projects quoted separately; rates on request | Placement fee for permanent hires; contractor day or hourly rates; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, SQL, Spark |
| Industries served | Manufacturing, Retail, Healthcare, Financial services, Technology | Financial services, Retail, Healthcare, Media, Technology |
deepsense.ai vs Harnham: overview
deepsense.ai
deepsense.ai has done AI work out of Warsaw since 2014, and its job listings describe a team of about 120 AI specialists who have delivered more than 200 commercial and research projects. Most of that team is employed directly, which matters if you want the same engineer for a year. The company sells team extension alongside its consulting work, and its recruiting ads ask for five or more years of production ML experience for senior roles. Strengths cluster around LLM and RAG systems, computer vision, defect detection and models that run on edge devices.
Harnham
Harnham has recruited for data and analytics roles since 2006 from London, with offices in the U.S. including New York and San Francisco. It places data engineers, data scientists and ML engineers on contract or permanent terms and runs a graduate training arm, Rockborne. As a recruitment agency, it screens through consultants who specialise in data hiring rather than through practising engineers, and contractors are not managed after placement the way a staffing firm's employees are. That makes it better for permanent hires than for managed augmentation.
Services and capabilities: deepsense.ai vs Harnham
| Capability | deepsense.ai | Harnham |
|---|---|---|
| ML engineers | ✓ | ✓ |
| LLM / GenAI engineers | ✓ | ✗ |
| AI agent developers | ✗ | ✗ |
| MLOps engineers | ✓ | ✗ |
| Computer vision engineers | ✓ | ✗ |
| NLP engineers | ✗ | ✗ |
| Data engineers | ✗ | ✓ |
| Engineer-led technical screen | ✓ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
| Direct hire option | ✗ | ✓ |
Tech stack comparison: deepsense.ai vs Harnham
| Framework / platform | deepsense.ai | Harnham |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | ✓ | N/A |
Pricing comparison: deepsense.ai vs Harnham
| Criterion | deepsense.ai | Harnham |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Direct hire, Contract-to-hire, Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: deepsense.ai vs Harnham
| Dimension | deepsense.ai | Harnham |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail, Healthcare | Financial services, Retail, Healthcare |
| Best use cases | Embedding an MLOps engineer in a platform team for a long engagement, Adding a computer-vision specialist for an edge defect-detection model | Hiring a permanent head of data science in London, Placing a contract data engineer for six months |
| Typical project type | Dedicated engineer | Direct hire |
deepsense.ai vs Harnham: pros and cons
| deepsense.ai | |
|---|---|
| + | Hiring ads for senior ML roles require five or more years of production experience |
| + | Engineers are mostly employees rather than contractors, which helps continuity |
| + | Deep computer-vision and edge-deployment experience, which few staffing firms can match |
| - | About 120 people, so large or sudden requests may wait |
| - | Staff augmentation is not its headline service; consulting projects get more of its marketing |
| - | No published rates or minimums |
| Harnham | |
|---|---|
| + | Long specialist history in data recruiting |
| + | Offices in the UK and several U.S. cities |
| + | Both contract and permanent hiring |
| - | Screening by recruitment consultants, not engineers |
| - | Contractors are not managed after placement |
| - | Headcount estimates vary |
Who should choose deepsense.ai?
A typical fit: embedding an MLOps engineer in a platform team for a long engagement.
A research-heavy bench of about 120 employed AI specialists with ten years of production work. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail, Healthcare, Financial services, Technology.
Who should choose Harnham?
A typical fit: hiring a permanent head of data science in London.
Twenty years of recruiting only in data and analytics. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Retail, Healthcare, Media, Technology.
Decision matrix: deepsense.ai vs Harnham
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | deepsense.ai |
| You need one specialist for a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Neither lists dedicated teams; check team size before signing |
| 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: deepsense.ai (Not published) vs Harnham (Not published) |
| Your team works U.S. hours | Neither lists Latin American engineers; confirm overlap hours in the contract |
| You may want to hire the engineer permanently later | Harnham |
Use case fit: deepsense.ai vs Harnham
| Use case | deepsense.ai fit | Harnham fit | Winner |
|---|---|---|---|
| Embedding an MLOps engineer in a platform team for a long engagement | Strong | Limited | deepsense.ai |
| Adding a computer-vision specialist for an edge defect-detection model | Strong | Limited | deepsense.ai |
| Hiring a permanent head of data science in London | Limited | Strong | Harnham |
| Placing a contract data engineer for six months | Limited | Strong | Harnham |
Verdict: deepsense.ai vs Harnham
deepsense.ai (4.6/5) is the stronger overall choice for most AI Engineer Staffing projects. A research-heavy bench of about 120 employed AI specialists with ten years of production work.
Harnham (3.7/5) is worth a look if you need placing a contract data engineer for six months. If your situation matches that, Harnham is a competitive option.
Related comparisons
deepsense.ai vs Harnham FAQ
Is deepsense.ai better than Harnham?
deepsense.ai (4.6/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: hiring ads for senior ML roles require five or more years of production experience. Harnham's strongest advantage: long specialist history in data recruiting.
How do deepsense.ai and Harnham differ in pricing?
deepsense.ai uses team extension billed monthly per engineer; projects quoted separately; rates on request pricing. Harnham uses placement fee for permanent hires; contractor day or hourly rates; 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: deepsense.ai or Harnham?
Harnham 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 Harnham?
deepsense.ai's primary differentiator is: a research-heavy bench of about 120 employed AI specialists with ten years of production work. Harnham's primary differentiator is: twenty years of recruiting only in data and analytics. They also differ in team size (100–200 vs 100–500), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Retail vs Financial services, Retail).
Verify all details directly with each company before making a decision.