Addepto vs KORE1: full comparison for 2026
Quick verdict
Addepto (4.0/5) edges ahead of KORE1 (3.6/5) overall. Addepto is the better choice for industrial and automotive companies that need data engineers who know factory data. KORE1 is the stronger option for U.S. companies that want a local agency to recruit ML engineers on contract-to-hire terms. The right choice depends on your project size, budget, and required tech stack.
Addepto vs KORE1: head-to-head summary
| Criterion | Addepto | KORE1 |
|---|---|---|
| Founded | 2017 | 2005 |
| HQ | Warsaw, Poland | Irvine, California, USA |
| Team size | 50–249 | Not published |
| Rating | 4.0 / 5 | 3.6 / 5 |
| Primary differentiator | Data and ML engineers with industrial and automotive client history | A U.S. staffing agency with contract-to-hire terms for AI roles |
| Pricing model | Monthly per engineer or project fee; rates on request | Contract bill rate or placement fee; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Databricks, Spark | Python, AWS, Azure |
| Industries served | Manufacturing, Automotive, Aviation, Retail, Logistics | Technology, Healthcare, Manufacturing, Finance, Aerospace |
Addepto vs KORE1: overview
Addepto
Addepto was founded in Warsaw in 2017 and works on AI, ML and data engineering, mostly for industrial and automotive clients. KMS Technology acquired it in December 2025, so it now sits inside a larger U.S.-based IT group. Addepto supplies data and ML engineers for team extension as well as running projects. The acquisition may widen its bench over time, but buyers should expect changes to contracts and account management as the integration proceeds.
KORE1
KORE1 is an IT and professional staffing agency headquartered in Irvine, California. Its own sources give both 1999 and 2005 as starting dates; we use 2005, the year in its company summary. It recruits on contract, contract-to-hire and direct-hire terms across IT, data and AI/ML, with pages for ML, LLM, MLOps and GenAI engineers. KORE1 reports an average time-to-hire of 17 days and 12-month retention of 92% for IT roles. Screening is done by recruiters, and AI is one category among many.
Services and capabilities: Addepto vs KORE1
| Capability | Addepto | KORE1 |
|---|---|---|
| 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: Addepto vs KORE1
| Framework / platform | Addepto | KORE1 |
|---|---|---|
| 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: Addepto vs KORE1
| Criterion | Addepto | KORE1 |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Contract-to-hire, Direct hire, Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Addepto vs KORE1
| Dimension | Addepto | KORE1 |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Automotive, Aviation | Technology, Healthcare, Manufacturing |
| Best use cases | Adding a data engineer to an automotive analytics platform, Building a predictive maintenance model with a two-person team | Hiring an on-site ML engineer in Southern California, Bringing in a contract MLOps engineer with a path to permanent |
| Typical project type | Dedicated engineer | Contract-to-hire |
Addepto vs KORE1: pros and cons
| Addepto | |
|---|---|
| + | Strong data engineering on Databricks and Azure |
| + | Industrial and automotive references |
| + | Backing from a larger group may add capacity |
| - | Acquired by KMS Technology in December 2025, so terms and contacts may change |
| - | Fewer computer-vision and NLP specialists than AI-research firms |
| - | Staffing evidence is thinner than its project work |
| KORE1 | |
|---|---|
| + | U.S.-based candidates for on-site or hybrid roles |
| + | Contract-to-hire lets you test before a permanent offer |
| + | Published time-to-hire figure |
| - | Recruiter-led screening |
| - | AI is one category inside a general staffing business |
| - | U.S. rates, which are higher than nearshore or offshore options |
Who should choose Addepto?
A typical fit: adding a data engineer to an automotive analytics platform.
Data and ML engineers with industrial and automotive client history. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Automotive, Aviation, Retail, Logistics.
Who should choose KORE1?
A typical fit: hiring an on-site ML engineer in Southern California.
A U.S. staffing agency with contract-to-hire terms for AI roles. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Healthcare, Manufacturing, Finance, Aerospace.
Decision matrix: Addepto vs KORE1
| 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 | 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 KORE1 (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 | KORE1 |
Use case fit: Addepto vs KORE1
| Use case | Addepto fit | KORE1 fit | Winner |
|---|---|---|---|
| Adding a data engineer to an automotive analytics platform | Strong | Limited | Addepto |
| Building a predictive maintenance model with a two-person team | Strong | Limited | Addepto |
| Hiring an on-site ML engineer in Southern California | Limited | Strong | KORE1 |
| Bringing in a contract MLOps engineer with a path to permanent | Limited | Strong | KORE1 |
Verdict: Addepto vs KORE1
Addepto (4.0/5) is the stronger overall choice for most AI Engineer Staffing projects. Data and ML engineers with industrial and automotive client history.
KORE1 (3.6/5) is worth a look if you need bringing in a contract MLOps engineer with a path to permanent. If your situation matches that, KORE1 is a competitive option.
Related comparisons
Addepto vs KORE1 FAQ
Is Addepto better than KORE1?
Addepto (4.0/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: strong data engineering on Databricks and Azure. KORE1's strongest advantage: U.S.-based candidates for on-site or hybrid roles.
How do Addepto and KORE1 differ in pricing?
Addepto uses monthly per engineer or project fee; rates on request pricing. KORE1 uses contract bill rate or placement fee; 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 KORE1?
Addepto 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 KORE1?
Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. KORE1's primary differentiator is: a U.S. staffing agency with contract-to-hire terms for AI roles. They also differ in team size (50–249 vs Not published), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Automotive vs Technology, Healthcare).
Verify all details directly with each company before making a decision.