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deepsense.ai Sp. z o.o.

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deepsense.aiWarsaw, Poland

Applied AI experts delivering end-to-end AI strategies and production-ready solutions for global enterprises.

Overview

deepsense.ai is a Europe-based applied AI company that partners with enterprises to turn AI ideas into production-ready solutions. It provides end-to-end guidance, development, and governance to help clients across industries navigate the AI landscape and achieve measurable business value. Capabilities span strategy, data science, MLOps, computer vision, edge solutions, and predictive analytics, enabling data-driven decision making. The team emphasizes practical, production-focused outcomes rather than theoretical research, operates with a remote-first culture, and maintains partnerships with leading AI platforms to accelerate deployment from discovery to production. The mission is to deliver value, empower clients from AI newcomers to industry leaders, and bridge the gap between cutting-edge AI and real-world applications.

Mission statement

Our mission is to deliver measurable value, partnering with clients from AI newcomers to industry leaders to navigate the evolving AI landscape. We aim to bridge the gap between cutting-edge AI solutions and practical applications, focusing on solving real-world problems rather than competing with research labs dedicated to academic pursuits.

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Analyze as a competitorCompare positioning, offers and segments against your own company.Evaluate as a vendorScore deepsense.ai Sp. z o.o. against alternatives on your own criteria.Claim this company's AI agentWork at deepsense.ai Sp. z o.o.? Improve your AI agent so it ranks higher when people ask AI about you.How AI sees this companyThe metadata, structured data and Markdown that assistants read.

What we offer

Ragbits

Accelerate the deployment of AI systems with Agentic RAG pipelines for effective data utilization.

deepsense.ai/rd-hub/ragbits/

MCP Servers

Service

Empower data-driven decision-making with custom MCP servers seamlessly integrated into your enterprise infrastructure.

deepsense.ai/tech-expertise/mlops/custom-mcp-servers-as-part-of-enterprise-ai-infrastructure/

Market segments

Market size by segment

Growth potential (CAGR)

Retrieval-augmented generation platforms

1 Billion USD43.4% CAGR

Capabilities that integrate enterprise data retrieval with large language models to provide contextually accurate, up-to-date responses using RAG, vector storage, and secure enterprise data connectors.

MLOps and LLM operations

2.98 Billion USD45.8% CAGR

Capabilities to manage model lifecycle, deploy and monitor machine learning and large language models, and optimize model performance and ROI in production.

Enterprise knowledge management

20 Billion USD15% CAGR

Capabilities that consolidate documents, media, transcripts, and chats into a single, contradiction-resolving knowledge base with semantic search and high-accuracy RAG for real-time retrieval.

On-prem AI infrastructure and data access

48.3 Billion USD24% CAGR

Scalable, secure on-premise compute and data access platforms that unify fragmented enterprise data sources and support high-demand analytics, inference and edge deployments.

More information about our offering

Ragbits

ragbits is an open-source platform for deploying Agentic RAG pipelines to production AI systems. It enables the design, deployment and operation of agentic, retrieval-augmented workflows across enterprise data environments.

  • Deploy Agentic RAG Pipelines
    Utilize proven architecture to rapidly create and deploy effective AI solutions.
  • Integrate Enterprise RAG Systems
    Ensure seamless integration of knowledge management processes within enterprise workflows.
  • Leverage LLMs
    Enhance productivity with AI-driven assistants and automated workflows.
  • Ensure AI Governance
    Systematic evaluation and optimization processes to maintain AI system integrity.
  • Streamline AI Operations
    Optimize and automate machine learning workflows for efficient deployment.
  • Accelerate RAG Development
    Rapidly prototype and build retrieval-augmented solutions without overhead.
  • Integrate Computer Vision
    Enhance AI workflows with advanced visual recognition and analysis.
  • Integrate Voice AI
    Enhance user interaction and automation in business operations.
  • Automate Document Processing
    Streamline knowledge retrieval and management from complex documents.
  • Support ML Workloads
    Harness advanced analytics for better decision-making across tasks.
  • Deploy Edge AI Solutions
    Run AI applications closer to data sources for real-time processing.

MCP Servers

Custom MCP servers unify access to critical data sources, enabling efficient queries and analytics without manual intervention, suitable for various industries.

  • Streamline Data Retrieval
    Eliminate the need for manual data extraction by enabling automated, standardized access to key data sources through the MCP servers.
  • Ensure Data Security
    The solution employs security measures that guarantee protected access to sensitive data, enhancing compliance and governance.
  • Enhance Operational Efficiency
    Facilitate large-scale analytics operations without sacrificing performance, ensuring seamless data processing even during peak times.

References

Methodology and sourcing behind the market figures shown above.

Retrieval-augmented generation platforms

Primary source (KBV Research) reports the RAG market at USD 994.0 million in 2023 with a 43.4% CAGR to reach USD 17.0 billion by 2031 — used as the basis for a ~1.0B current market size and 43.4% CAGR estimate. Market.us and an industry analysis (LinkedIn excerpt) show similar high-growth projections (CAGR ~35–49%), supporting strong near-term expansion.

MLOps and LLM operations

Primary estimate uses Fortune Business Insights (2025 valuation USD 2.98B and forecast CAGR 45.8%). Market Research Future provides a corroborating market-size trajectory (2024: USD 3.13B; 2025: USD 4.37B) with a slightly lower CAGR (39.8%). Additional sources show varying growth assumptions (arXiv citing a 43% five‑year growth projection; a LinkedIn summary referencing an 11% CAGR for a different forecast horizon). I selected Fortune’s 2025 size and 45.8% CAGR as the primary figures because the source provides explicit year-by-year baseline and a published multi‑year CAGR for MLOps/LLMOps in the provided search results.

Enterprise knowledge management

Synthesis of market reports in the provided results for the 'knowledge management' / enterprise KM software category. Market size estimates in 2025 range from ~USD 14.6B (MarketResearchFuture) to USD 23.2B (Fortune). One outlier report (Business Research Insights) reports a much larger figure; I treated that as an expanded definitional outlier. I therefore estimated a current addressable market ~USD 20B (midpoint of credible reports) and a growth potential (CAGR) of ~15%, the midpoint of reported CAGRs (~13.8%–16.9%), noting other sources report 10.3%–18.1%.

On-prem AI infrastructure and data access

Estimates use published AI data-center/infrastructure market figures in the search results and apply an on‑prem share assumption. DataM reports a global AI data centers market of US$120.74B (2025) with 22.8% CAGR; NextMSC reports USD142.8B (2025) and a 24.8% CAGR; Spherical reports broader AI infrastructure growth (USD34.6B in 2023 to USD536.5B by 2033, 31.54% CAGR) and states the on‑premise segment held largest 2023 share. I assume on‑prem deployments represent roughly 40% of the AI data‑center/infrastructure market (enterprises and regulated sectors favor on‑prem), yielding ~US$48.3B (2025 equivalent) and a projected CAGR ~24% (aligned to the 22.8–24.8% range observed).

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