deepsense.ai
Warsaw AI engineering firm known for retrieval-augmented LLM systems and computer vision
Founded 2014 | Warsaw, Poland | 101–200 employees
llm-api-integrationdocument-processingagentic-aimlops-llmops
What is deepsense.ai?
deepsense.ai is an AI-first engineering company founded in 2014 out of the AI division of CodiLime, with headquarters in Warsaw and an office in Palo Alto. It employs roughly 120–200 people, including several Kaggle competition winners. Its integration work centres on LLM applications using retrieval-augmented generation (RAG), plus computer vision and edge deployments for manufacturing. It lists technical partnerships with OpenAI, NVIDIA, Anyscale and LangChain.
deepsense.ai works primarily with clients in Manufacturing, Retail, Financial services, Healthcare sectors. Its primary differentiator is: Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets.
deepsense.ai tech stack and services
LangChainAzure OpenAIAWS BedrockNVIDIA TritonRayPython
| Service area |
|---|
| LLM API Integration |
| Document Processing |
| Agentic AI |
| MLOps / LLMOps |
deepsense.ai pricing
Short answer: T&M and dedicated teams; rates on request. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
deepsense.ai does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
deepsense.ai pros and cons
| Advantages | Things to consider |
|---|---|
| +Deep ML talent, with evaluation of retrieval quality treated as part of the build | -Less experience embedding AI inside packaged CRM or ERP products |
| +Experience deploying models on edge hardware as well as in the cloud | -Engagements lean toward engineering capacity, with less change-management support |
| +Open publication record and active LangChain contribution history | |
| +Comfortable working alongside an in-house data team |
deepsense.ai vs alternatives
How deepsense.ai compares to the other top AI Integration companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Mid-market firms adding AI to existing CRM and... | Integrates with the CRM and ERP you already run, with PII redaction and per-user access rules applied before any model call | 4.8 | Full comparison |
| Provectus | AWS-based companies needing data work before AI. | Pairs a Premier Tier AWS partnership with ML and GenAI competencies, so the data platform and the model integration come from one team | 4.6 | Full comparison |
| Slalom | Salesforce-centric enterprises, Data Cloud and Agentforce. | Partner standing across Salesforce, AWS, Microsoft and Snowflake at once, which covers most of a typical enterprise stack | 4.6 | Full comparison |
| Neurons Lab | Banks and insurers piloting agentic AI under regulation. | Financial-services agent work delivered by an AWS Advanced Tier partner that also holds a public-sector designation | 4.5 | Full comparison |
| TTMS | Pharma and regulated firms on Salesforce or Microsoft... | Adds AI inside Salesforce, Microsoft 365 and Adobe Experience Manager for pharma and defense clients with strict validation rules | 4.5 | Full comparison |
| Avanade | Microsoft-standardized enterprises rolling out Copilot. | A Microsoft-only practice of about 59,000 people covering Dynamics 365, Azure OpenAI and Copilot governance | 4.4 | Full comparison |
| Addepto | Data teams needing warehouse work before an LLM... | Data engineering and MLOps come first, so AI features sit on warehouses that are already clean and monitored | 4.3 | Full comparison |
| Vstorm | Teams wanting agents they will own and maintain. | Agent specialists who hand over a production system the client team can maintain without them | 4.3 | Full comparison |
| Quantiphi | Google Cloud estates, high-volume document AI. | Premier partner on both Google Cloud and AWS, with a long run of Document AI and contact-centre deployments | 4.3 | Full comparison |
| Grid Dynamics | Retailers adding AI to commerce and supply chain... | Packaged agentic-commerce accelerators backed by a large engineering bench with public financial reporting | 4.3 | Full comparison |
| EPAM Systems | Large enterprises with Salesforce and SAP estates. | Engineering depth across Salesforce, SAP and major model providers, including a formal partnership with Anthropic | 4.3 | Full comparison |
| Accenture | Global enterprises with multi-country compliance needs. | Scale and compliance coverage across every major platform, region and regulator | 4.2 | Full comparison |
| Perficient | Marketing and service teams on Adobe or Salesforce. | Adds AI inside customer-experience platforms such as Adobe Experience Cloud, Salesforce and Microsoft | 4.2 | Full comparison |
| Azumo | Budget-conscious U.S. teams, time-zone-aligned. | U.S.-hours engineering from Argentina at a $25–$49 Clutch band with a $10,000 entry point | 4.2 | Full comparison |
| RTS Labs | U.S. mid-market firms with stalled AI pilots. | Onshore U.S. team focused on getting a stalled pilot into production with ERP and CRM connections | 4.2 | Full comparison |
| Thoughtworks | Engineering-led firms that value delivery practice. | Long-standing engineering discipline, testing and continuous delivery applied to AI features | 4.1 | Full comparison |
| InData Labs | Mid-size firms needing forecasting and data science. | Data-science-led team that builds predictive models alongside generative features | 4.1 | Full comparison |
| Master of Code Global | Consumer brands building chat and voice assistants. | Two decades of conversational design work for consumer brands, now applied to LLM-based assistants | 4.1 | Full comparison |
| Deloitte | Regulated enterprises needing audit-grade AI controls. | Risk and governance expertise next to SAP and Oracle integration teams in one firm | 4.1 | Full comparison |
| IBM Consulting | Enterprises already committed to IBM watsonx. | Prebuilt connectors in watsonx Orchestrate plus IBM's own governance tooling | 4.0 | Full comparison |
| Globant | Firms wanting subscription-priced AI capacity. | Subscription AI Pods supervised by human experts, sold as a product instead of billed by the hour | 4.0 | Full comparison |
| N-iX | Larger programmes needing an Eastern European team. | Large Central and Eastern European engineering bench with data-platform experience | 4.0 | Full comparison |
| ScienceSoft | Healthcare and finance firms wanting one IT vendor. | Long-established generalist covering both the surrounding software and the AI feature | 4.0 | Full comparison |
| Itransition | Cost-sensitive buyers wanting a large generalist. | Low published rates combined with a large engineering pool | 3.9 | Full comparison |
| Miquido | Product teams adding AI to customer-facing apps. | Product design and mobile engineering applied to AI features in apps | 3.9 | Full comparison |
| Markovate | Startups wanting a quick generative AI build. | Generative AI app builds for startups with a fast proof-of-concept focus | 3.9 | Full comparison |
| LeewayHertz | Buyers open to a platform-led ZBrain build. | Builds on its own ZBrain low-code platform, now backed by The Hackett Group | 3.8 | Full comparison |
deepsense.ai FAQ
What is deepsense.ai?
Warsaw AI engineering firm known for retrieval-augmented LLM systems and computer vision
How much does deepsense.ai charge?
Pricing at deepsense.ai: T&M and dedicated teams; rates on request. 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 LangChain, Azure OpenAI, AWS Bedrock, NVIDIA Triton, Ray, Python. Primary industries served include Manufacturing, Retail, Financial services, Healthcare.
Is deepsense.ai right for enterprise?
Engineering teams wanting a strong RAG partner. 101–200 team size. Key consideration: Less experience embedding AI inside packaged CRM or ERP products.
What are the best deepsense.ai alternatives?
The best alternatives to deepsense.ai depend on your use case. Top options are:
- Tensorway: integrates with the CRM and ERP you already run, with PII redaction and per-user access rules applied before any model call
- Provectus: pairs a Premier Tier AWS partnership with ML and GenAI competencies, so the data platform and the model integration come from one team
- Slalom: partner standing across Salesforce, AWS, Microsoft and Snowflake at once, which covers most of a typical enterprise stack
Compare deepsense.ai with other AI Integration companies
deepsense.ai vs Tensorway deepsense.ai vs Provectus deepsense.ai vs Slalom deepsense.ai vs Neurons Lab deepsense.ai vs TTMS deepsense.ai vs Avanade deepsense.ai vs Addepto deepsense.ai vs Vstorm deepsense.ai vs Quantiphi deepsense.ai vs Grid Dynamics deepsense.ai vs EPAM Systems deepsense.ai vs Accenture deepsense.ai vs Perficient deepsense.ai vs Azumo deepsense.ai vs RTS Labs deepsense.ai vs Thoughtworks deepsense.ai vs InData Labs deepsense.ai vs Master of Code Global deepsense.ai vs Deloitte deepsense.ai vs IBM Consulting deepsense.ai vs Globant deepsense.ai vs N-iX deepsense.ai vs ScienceSoft deepsense.ai vs Itransition deepsense.ai vs Miquido deepsense.ai vs Markovate deepsense.ai vs LeewayHertz
Verify all details directly with deepsense.ai before making a decision.