Addepto vs InData Labs: full comparison for 2026
Quick verdict
Addepto (4.3/5) edges ahead of InData Labs (4.1/5) overall. Addepto is the better choice for data teams needing warehouse work before an LLM project. InData Labs is the stronger option for mid-size firms needing forecasting and data science. The right choice depends on your project size, budget, and required tech stack.
Addepto vs InData Labs: head-to-head summary
| Criterion | Addepto | InData Labs |
|---|---|---|
| Founded | 2018 | 2014 |
| HQ | Warsaw, Poland | Nicosia, Cyprus |
| Team size | 50–249 | 50–249 |
| Rating | 4.3 / 5 | 4.1 / 5 |
| Primary differentiator | Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored | Data-science-led team that builds predictive models alongside generative features |
| Pricing model | $50–$99/hr (Clutch band); discovery workshops, then T&M | Fixed-price and T&M; rates on request |
| Min. engagement | $10,000+ (Clutch) | Not disclosed |
| Primary tech stack | Databricks, Snowflake, Azure OpenAI | Python, Azure OpenAI, AWS Bedrock |
| Industries served | Manufacturing, Retail & e-commerce, Aviation, Financial services | Retail & e-commerce, Healthcare, Financial services, Logistics |
Addepto vs InData Labs: overview
Addepto
Addepto is a Warsaw-based AI and data consultancy that started trading in April 2018 (some directories list 2017). Clutch shows 50–249 employees, a $50–$99 hourly band and a $10,000 minimum project. CB Insights reports that KMS Technology acquired the company in December 2025, after an earlier tie-up with Grape Up. Its work typically begins with data engineering and moves on to generative AI, MLOps and AI discovery workshops.
InData Labs
InData Labs is a data science and AI company founded in 2014 and headquartered in Nicosia, Cyprus, with offices in Vilnius and Miami. Clutch lists 50–249 employees, and the firm says it has delivered 150+ projects since 2014 (per company website; independently unverifiable). Clutch shows AI development as more than half of its work, followed by BI and big data consulting. Reviewers praise its data science skill and mention slower proposal and planning cycles.
Services and capabilities: Addepto vs InData Labs
| Capability | Addepto | InData Labs |
|---|---|---|
| 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: Addepto vs InData Labs
| Framework / platform | Addepto | InData Labs |
|---|---|---|
| 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 |
| Databricks | ✓ | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | N/A | ✓ |
| LangChain | ✓ | N/A |
| ServiceNow | N/A | N/A |
Pricing comparison: Addepto vs InData Labs
| Criterion | Addepto | InData Labs |
|---|---|---|
| Minimum engagement | $10,000+ (Clutch) | Not disclosed |
| Engagement models | Fixed project, Time & materials | Fixed project, Time & materials |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: Addepto vs InData Labs
| Dimension | Addepto | InData Labs |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail & e-commerce, Aviation | Retail & e-commerce, Healthcare, Financial services |
| Best use cases | Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant., Productionizing ML models with MLflow and monitoring. | Churn or demand models that feed a BI dashboard., Document extraction for invoices and receipts. |
| Typical project type | Fixed project | Fixed project |
Addepto vs InData Labs: pros and cons
| Addepto | |
|---|---|
| + | Publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward |
| + | Databricks and Spark experience helps when the data estate is the real blocker |
| + | Discovery workshops scope use cases before larger spend |
| + | Predictive analytics and LLM work available from the same team |
| - | Acquired by KMS Technology in December 2025 (per CB Insights), so ownership and leadership may change |
| - | Corporate history includes several restructurings, which complicates long-term vendor planning |
| - | Limited published work inside CRM platforms |
| InData Labs | |
|---|---|
| + | Long track record in classical data science as well as LLM work |
| + | EU-registered company with Lithuanian delivery |
| + | Strong Clutch reviews on technical quality |
| - | Reviewers note slower proposals and planning |
| - | Limited published integration work inside large CRM or ERP suites |
| - | Headcount estimates vary widely between directories |
Who should choose Addepto?
A typical fit: building a Databricks lakehouse that later feeds demand forecasts and an internal assistant.
Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. Minimum engagement starts at $10,000+ (Clutch). Works best with clients in Manufacturing, Retail & e-commerce, Aviation, Financial services.
Who should choose InData Labs?
A typical fit: churn or demand models that feed a BI dashboard.
Data-science-led team that builds predictive models alongside generative features. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Healthcare, Financial services, Logistics.
Decision matrix: Addepto vs InData Labs
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Neither advertises one; ask for a scoped pilot |
| 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 | Ask both for their PII and access-control design |
| Your budget is at the lower end | Compare: Addepto ($10,000+ (Clutch)) vs InData Labs (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 | Neither lists agentic AI work |
Use case fit: Addepto vs InData Labs
| Use case | Addepto fit | InData Labs fit | Winner |
|---|---|---|---|
| Building a Databricks lakehouse that later feeds demand forecasts and an internal assistant. | Strong | Limited | Addepto |
| Productionizing ML models with MLflow and monitoring. | Strong | Limited | Addepto |
| Churn or demand models that feed a BI dashboard. | Limited | Strong | InData Labs |
| Document extraction for invoices and receipts. | Limited | Strong | InData Labs |
Verdict: Addepto vs InData Labs
Addepto (4.3/5) is the stronger overall choice for most AI Integration projects. Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored.
InData Labs (4.1/5) is worth a look if you need document extraction for invoices and receipts. If your situation matches that, InData Labs is a competitive option.
Related comparisons
Addepto vs InData Labs FAQ
Is Addepto better than InData Labs?
Addepto (4.3/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: publicly listed Clutch rate band and $10,000 minimum make budgeting straightforward. InData Labs's strongest advantage: long track record in classical data science as well as LLM work.
How do Addepto and InData Labs differ in pricing?
Addepto pricing: $50–$99/hr (Clutch band); discovery workshops, then T&M. Minimum engagement: $10,000+ (Clutch). InData Labs pricing: Fixed-price and T&M; rates on request. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or InData Labs?
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 InData Labs?
Addepto's primary differentiator is: data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored. InData Labs's primary differentiator is: data-science-led team that builds predictive models alongside generative features. They also differ in team size (50–249 vs 50–249), minimum engagement ($10,000+ (Clutch) vs Not disclosed), and primary industries served (Manufacturing, Retail & e-commerce vs Retail & e-commerce, Healthcare).
Verify all details directly with each company before making a decision.