DeepSense.ai
DeepSense.ai delivers production-grade AI systems — LLMs, RAG, MLOps, computer vision, and edge AI — for enterprises across software, manufacturing, pharma, and telecoms.
About
DeepSense.ai is a Warsaw-based applied AI consultancy with a US presence, founded in 2014. They partner with enterprises to design, build, and scale production-ready AI systems — spanning LLMs and RAG pipelines, MLOps automation, computer vision, edge AI, and predictive analytics. With 200+ commercial AI projects completed and a team of 120+ AI experts including Kaggle winners and PhDs, they serve global organizations including Johnson & Johnson, Sky, Zebra Technologies, Volkswagen, Nielsen, Danone, Google, and Santander.
DeepSense.ai holds official partner status with OpenAI, Anthropic, LangChain, NVIDIA, and Anyscale. Their in-house R&D hub produces open-source tools — including ragbits, a proprietary modular framework for building GenAI and agentic systems, and db-ally, a structured database querying library — which they use to accelerate client project delivery. An NPS of 63 and 67% of revenue from multi-year client relationships reflect their focus on long-term partnerships over one-off engagements.
What They Do
LLMs & RAG
Builds AI agents, co-pilots, and decision-support tools using large language models and real-time retrieval systems
Develops RAG pipelines for document understanding and internal knowledge access
Deploys AI Voice Bots for enterprise operations
Builds Custom MCP Servers as part of enterprise AI infrastructure
MLOps Engineering
Automates ML workflows from model training through CI/CD pipelines and monitoring
Designs scalable, production-resilient AI systems on GCP and Kubernetes
Optimizes existing AI operations and edge deployments
Computer Vision
Applies image recognition, 3D modeling, and defect detection for manufacturing and autonomous systems
Projects include wildlife recognition in aerial imagery (NOAA) and FMCG image recognition (Nielsen)
Edge AI & Predictive Analytics
Deploys inference models onto IoT networks, embedded systems, and remote environments
Delivers predictive maintenance, anomaly detection, and demand forecasting solutions
AI Guidance & Strategy
Conducts AI readiness audits, technical discovery workshops, and roadmap planning
Provides AI advisory for business and technical teams evaluating use cases and ROI
Services & Tech Stack
Services
- RAG Pipeline Development
- Autonomous AI Agents
- ML Pipeline Development
- AI Use Case Identification
- Custom AI App Building
Is This a Fit?
Enterprise product and data engineering teams in software, manufacturing, pharma, and telecoms that need production-ready AI systems — particularly LLM agents, RAG pipelines, and MLOps infrastructure — built and deployed at scale.
Companies seeking simple chatbot deployments, off-the-shelf AI tool configuration, or one-time advisory without implementation. Not suited for early-stage startups with budgets below $25,000.
Ideal Client
Chief Data Officers, VPs of Engineering, and AI/Automation Leads at mid-market to enterprise companies in software, manufacturing, pharma, or telecoms seeking to embed AI into products or operations with a trusted long-term implementation partner.
Track Record
Founded in 2014, DeepSense.ai has completed 200+ commercial AI projects with a team of 120+ AI specialists including Kaggle winners and PhDs. They hold official partner status with OpenAI, Anthropic, NVIDIA, LangChain, and Anyscale, and maintain an NPS of 63 with 67% of revenue from multi-year client relationships.
Common Outcomes
- 98% reduction in image analysis time for aerial wildlife recognition (NOAA)
- 85% reduction in connector development time — from 2 weeks to 3 days — using modular plugin architecture
- AI agent customer support platform delivered from advisory to MVP in 3 months
- 25% of autonomous commerce actions executed correctly within 6 weeks of deployment
Notable Clients
Use Cases
Case Studies
From Fragmented AI Experiments to a Coherent Enterprise AI Roadmap
Enterprise / TechnologyHelped an enterprise consolidate scattered AI initiatives into a structured, prioritized AI roadmap aligned to business outcomes.
From AI Advisory to MVP in 3 Months: Accelerating Time to Market for an AI Agent Customer Support Platform
Software & TechnologyDelivered an AI agent customer support platform MVP in 3 months, moving from initial advisory through to production deployment.
Accelerating Internal Evidence Generation with Autonomous AI Agents
Life SciencesChallenge
Automating literature review and evidence synthesis within the IEGP process.
Solution
Built an AI-powered app using autonomous LLM-based agents to automate evidence generation workflows.
LLM Evaluation for Document Understanding
EnterpriseEliminated guesswork in LLM selection by providing clear guidance for optimal model choice in document understanding tasks.
Reducing Time to Build Data & AI Connectors from 2 Weeks to 3 Days with a Modular Plugin Architecture
Software & TechnologyChallenge
Slow connector development time across a growing set of data sources and destinations.
Solution
Implemented a modular plugin architecture that standardized connector development.
Enterprise-Grade Cloud Infrastructure Powering Scalable AI at Scale
Enterprise / TechnologyDesigned and deployed enterprise-grade cloud infrastructure to support scalable AI workloads in production environments.
AI-Powered Image Recognition for Faster FMCG Insights (Nielsen)
Retail / FMCGBuilt an AI-powered image recognition system for Nielsen to accelerate FMCG market insight generation.
AI Copilot's Impact on Productivity in Revolutionizing ADA Language Development
Software & TechnologyDelivered an AI copilot that measurably improved developer productivity in ADA language development workflows.
Recognizing Wildlife in Aerial Imagery with 98% Reduction in Image Analysis Time (NOAA)
Government / EnvironmentalDelivered a computer vision system for NOAA that achieved a 98% reduction in the time required to analyze aerial wildlife imagery.
Reinforcement Learning Speeds Up Autonomous Driving (Volkswagen)
Manufacturing / AutomotiveApplied reinforcement learning techniques to accelerate autonomous driving development for Volkswagen.
At a Glance
Location
Warsaw, Poland
Founded
2014
Team Size
51 – 200Typical Budget
$25,000–$199,999
Timeline
6–18 months for full AI system delivery; shorter engagements (4–8 weeks) available for AI advisory and roadmap projects
Delivery
RemoteHybridEngagement
Project BasedRetainerPricing
$100 - $149Client Tier
Mid MarketEnterpriseRegions Served
Northern AmericaWestern EuropeEastern EuropeLanguages
EnglishPolishCertifications
OpenAI Services PartnerAnthropic Claude Services PartnerNVIDIA Service Delivery PartnerLangChain PartnerAnyscale Partner
Focus Areas
Specialties
Verticals
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| Signal | |||
|---|---|---|---|
| Category | AI Product Development | AI Product Development | AI Product Development |
| Location | Warsaw, Poland | Chino Hills, United States | San Francisco, United States |
| Team Size | Not listed | Not listed | Not listed |
| Client Tier | Mid Market | Startup | Enterprise |
| Delivery Model | Remote | Remote | Hybrid |
| Typical Budget | $25,000 – $199,999 | $5,000 – $50,000 | $500,000+ |
| Services | RAG Pipeline DevelopmentAutonomous AI AgentsML Pipeline Development+2 | RAG Pipeline DevelopmentAI Workflow AutomationCustom AI App Building+2 | Custom AI App BuildingMulti Agent Workflow OrchestrationAutonomous AI Agents+2 |
| Tech Stack | LangChainOpenAI APIAnthropic API+5 | Not listed | OpenAI API |