Andela vs Harnham: full comparison for 2026
Quick verdict
Andela (4.1/5) edges ahead of Harnham (3.7/5) overall. Andela is the better choice for companies building a long-term remote engineering group outside the U.S. that includes some ML roles. 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.
Andela vs Harnham: head-to-head summary
| Criterion | Andela | Harnham |
|---|---|---|
| Founded | 2014 | 2006 |
| HQ | New York, USA | London, United Kingdom |
| Team size | 300–500 staff; large engineer marketplace | 100–500 |
| Rating | 4.1 / 5 | 3.7 / 5 |
| Primary differentiator | Assessment tooling from its 2026 Woven acquisition plus an in-house AI training academy | Twenty years of recruiting only in data and analytics |
| Pricing model | Monthly rate per engineer; marketplace and managed options; 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, TensorFlow, PyTorch | Python, SQL, Spark |
| Industries served | Technology, Financial services, Media, Healthcare, Retail | Financial services, Retail, Healthcare, Media, Technology |
Andela vs Harnham: overview
Andela
Andela started in 2014 in Lagos and is now headquartered in New York, running a private marketplace of engineers from Africa, Latin America and other regions. In January 2026 it acquired Woven, a company that builds technical assessments, to strengthen how it checks real engineering ability. It also runs an AI Academy and in 2025 committed to training 3,000 technologists in AI coding with GitHub. Profile counts in the six figures are unverified. Andela suits companies that want long-term remote engineers at lower cost than U.S. hiring, with screening that is becoming more rigorous but is still largely general software assessment.
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: Andela vs Harnham
| Capability | Andela | 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: Andela vs Harnham
| Framework / platform | Andela | Harnham |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Andela vs Harnham
| Criterion | Andela | Harnham |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Freelance contract | Direct hire, Contract-to-hire, Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Andela vs Harnham
| Dimension | Andela | Harnham |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Technology, Financial services, Media | Financial services, Retail, Healthcare |
| Best use cases | Hiring a remote data engineer for a long product roadmap, Adding an ML engineer to an existing Andela-staffed team | Hiring a permanent head of data science in London, Placing a contract data engineer for six months |
| Typical project type | Dedicated engineer | Direct hire |
Andela vs Harnham: pros and cons
| Andela | |
|---|---|
| + | Woven's assessments test practical engineering rather than quiz answers |
| + | Strong in Africa and Latin America, with lower rates than U.S. hiring |
| + | Trains its own engineers in AI tooling |
| - | The Woven integration is new, so its effect on ML vetting is unproven |
| - | Most of the pool is general software talent, not ML specialists |
| - | Network-size figures come from secondary sources |
| 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 Andela?
A typical fit: hiring a remote data engineer for a long product roadmap.
Assessment tooling from its 2026 Woven acquisition plus an in-house AI training academy. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Financial services, Media, Healthcare, Retail.
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: Andela vs Harnham
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Neither documents an engineer-led screen; run your own technical interview |
| 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 | Andela |
| 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: Andela (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: Andela vs Harnham
| Use case | Andela fit | Harnham fit | Winner |
|---|---|---|---|
| Hiring a remote data engineer for a long product roadmap | Strong | Strong | Both equally |
| Adding an ML engineer to an existing Andela-staffed team | Strong | Limited | Andela |
| Hiring a permanent head of data science in London | Strong | Strong | Both equally |
| Placing a contract data engineer for six months | Limited | Strong | Harnham |
Verdict: Andela vs Harnham
Andela (4.1/5) is the stronger overall choice for most AI Engineer Staffing projects. Assessment tooling from its 2026 Woven acquisition plus an in-house AI training academy.
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
Andela vs Harnham FAQ
Is Andela better than Harnham?
Andela (4.1/5) scores higher overall, but "better" depends on your use case. Andela's strongest advantage: Woven's assessments test practical engineering rather than quiz answers. Harnham's strongest advantage: long specialist history in data recruiting.
How do Andela and Harnham differ in pricing?
Andela uses monthly rate per engineer; marketplace and managed options; 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: Andela or Harnham?
Andela 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 Andela and Harnham?
Andela's primary differentiator is: assessment tooling from its 2026 Woven acquisition plus an in-house AI training academy. Harnham's primary differentiator is: twenty years of recruiting only in data and analytics. They also differ in team size (300–500 staff; large engineer marketplace vs 100–500), minimum engagement (Not published vs Not published), and primary industries served (Technology, Financial services vs Financial services, Retail).
Verify all details directly with each company before making a decision.