deepsense.ai
Warsaw applied-AI company that lends its data scientists and ML engineers to client teams
What is deepsense.ai?
deepsense.ai was founded in 2014, grew out of the AI division of CodiLime, and is headquartered in Warsaw with an office in Palo Alto. Third-party directories put its headcount between roughly 100 and 200 people, and the company says it employs more than 120 AI experts, including Kaggle competition winners and PhD holders. Besides project work in generative AI, MLOps, computer vision and edge AI, it runs a dedicated AI staff augmentation service in which its own engineers extend a client's team.
deepsense.ai works primarily with clients in Manufacturing, Retail & e-commerce, Healthcare & life sciences, Financial services, Software & SaaS sectors. Its primary differentiator is: A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench.
deepsense.ai tech stack and services
| Service area |
|---|
| ML Engineers |
| Computer Vision |
| LLM Engineers |
| MLOps |
| Eastern Europe Talent |
deepsense.ai pricing
Short answer: deepsense.ai uses a time and materials for augmented engineers; project contracts; rates on request pricing approach. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Full-time dedicated engineers | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| Managed delivery | Variable; depends on team size | Large programmes or team augmentation |
deepsense.ai pros and cons
| Advantages | Things to consider |
|---|---|
| +Every engineer it places comes from an AI-only company | -A bench of roughly 120 AI staff limits how many people can start at once |
| +Strong record in computer vision and edge deployment | -Polish rates are higher than Ukrainian or Latin American alternatives |
| +Clutch reviewers describe team-augmentation work with strong engineering skills | -Better suited to hard modeling work than to routine LLM integration |
deepsense.ai vs alternatives
How deepsense.ai compares to the other top AI Staff Augmentation companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| EPAM Systems | Large enterprises, regulated industries, multi-team AI programs. | Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes | 4.6 | Full comparison |
| Turing | Fast access to LLM and ML specialists from... | An AI-first network whose engineers also do model training and evaluation work for frontier labs | 4.5 | Full comparison |
| Tensorway | Product teams adding senior AI specialists without vendor... | Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories | 4.4 | Full comparison |
| BairesDev | U.S. companies needing several AI engineers on matching... | A large salaried Latin American bench that works U.S. time zones | 4.3 | Full comparison |
| N-iX | Data-heavy AI work needing a large European team. | Data engineering and ML from a 2,000-person European employer with two decades of delivery history | 4.2 | Full comparison |
| Andela | Enterprises building blended global teams with AI skills. | A marketplace that certifies engineers on AI skills before placement | 4.2 | Full comparison |
| Toptal | Short engagements with one senior AI specialist. | A heavily screened freelance pool that can supply one senior expert quickly | 4.2 | Full comparison |
| Globant | Enterprises wanting AI capacity on a subscription model. | Subscription-based AI Pods as an alternative to per-engineer billing | 4.1 | Full comparison |
| Azumo | Nearshore LLM and NLP builds for U.S. mid-market. | A nearshore team that also builds its own NLP products | 4.1 | Full comparison |
| InData Labs | Mid-sized companies adding data scientists to product teams. | A data-science-only firm small enough that senior staff stay involved | 4.1 | Full comparison |
| Innowise | Companies needing AI engineers plus surrounding app developers. | A large in-house bench that can staff AI and conventional engineering roles together | 4.1 | Full comparison |
| Uvik Software | Python-heavy AI teams wanting transparent pricing. | Published rate band, minimum term and replacement guarantee | 4.0 | Full comparison |
| DataArt | Finance and healthcare firms extending data and AI... | Nearly three decades of domain work in finance, healthcare and travel | 4.0 | Full comparison |
| Encora | U.S. firms wanting nearshore AI teams from a... | Large Mexican and Latin American delivery base with an AI engineering practice | 4.0 | Full comparison |
| Wizeline | U.S. companies wanting Mexico-based AI engineers. | A Guadalajara delivery base close to U.S. clients in time and travel | 4.0 | Full comparison |
| Intellias | Automotive and location-tech teams adding ML engineers. | Domain depth in automotive and mapping software | 4.0 | Full comparison |
| Kanerika | Microsoft Fabric and Databricks shops needing AI-ready data. | Platform specialists for Fabric, Databricks and Snowflake | 3.9 | Full comparison |
| Nearsure | U.S. teams adding Latin American GenAI developers. | Augmentation-first business model with a growing AI studio | 3.9 | Full comparison |
| nCube | Companies building a long-term offshore AI team. | Builds and runs a client-branded R&D team, including HR and office setup | 3.9 | Full comparison |
| Svitla Systems | Long-running team extension with mixed AI and app... | Two decades of team-extension relationships with U.S. clients | 3.9 | Full comparison |
| STX Next | Python codebases adding LLM and data engineers. | Python specialization applied to data and AI delivery | 3.9 | Full comparison |
| Howdy.com | U.S. startups hiring full-time Latin American AI engineers. | Full-time, single-client placements with employment handled by Howdy | 3.9 | Full comparison |
| Revelo | Hiring Latin American developers through a marketplace. | A very large Latin American pool with payroll and compliance included | 3.8 | Full comparison |
| BEON.tech | U.S. teams wanting Argentina-based data and ML engineers. | Nearshore recruitment focused on AI and data science roles | 3.8 | Full comparison |
| Xenoss | AdTech and MarTech firms needing real-time data plus... | Real-time, high-load data engineering from AdTech roots | 3.8 | Full comparison |
| Simform | Cloud-first companies adding AI and data engineers. | Cloud and data engineering paired with AI/ML from an India-based bench | 3.8 | Full comparison |
| Vention | Venture-backed startups scaling product and AI engineers. | Long record of extending startup engineering teams | 3.8 | Full comparison |
| ScienceSoft | Regulated companies wanting a documented hiring process. | Publishes its staff augmentation timeline and process | 3.7 | Full comparison |
| Mobilunity | Budget-conscious teams hiring one dedicated developer. | Lowest published rate band among the companies reviewed | 3.7 | Full comparison |
| Neoteric | Small GenAI pilots with a low entry cost. | Low $10,000 minimum for AI discovery and proof-of-concept work | 3.7 | Full comparison |
| LeewayHertz | Hackett Group clients adding GenAI developers. | GenAI app development backed by a public consulting parent | 3.6 | Full comparison |
deepsense.ai FAQ
What is deepsense.ai?
Warsaw applied-AI company that lends its data scientists and ML engineers to client teams
How much does deepsense.ai charge?
deepsense.ai uses time and materials for augmented engineers; project contracts; rates on request pricing. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does deepsense.ai use?
deepsense.ai works with Python, PyTorch, TensorFlow, LangChain, Hugging Face, MLflow, Kubernetes, AWS. Primary industries served include Manufacturing, Retail & e-commerce, Healthcare & life sciences, Financial services, Software & SaaS.
Is deepsense.ai right for enterprise?
Research-heavy ML problems, computer vision, edge AI. 100–200 team size. Key consideration: A bench of roughly 120 AI staff limits how many people can start at once.
What are the best deepsense.ai alternatives?
The best alternatives to deepsense.ai depend on your use case. Top options are:
- EPAM Systems: thousands of certified genai engineers inside a publicly listed firm with enterprise security and procurement processes
- Turing: an ai-first network whose engineers also do model training and evaluation work for frontier labs
- Tensorway: senior ai engineers run the technical screening, and every model and line of code stays in the client's repositories
Compare deepsense.ai with other AI Staff Augmentation companies
Verify all details directly with deepsense.ai before making a decision.