Daten & Wissen , a pioneering AI-driven company, is on a mission to bridge the gap between complex artificial intelligence solutions and the everyday needs of small and medium enterprises. Founded in November 2019 by visionaries Chirag Tank and Jitendra Purohit , the company was built with a bold idea: to make enterprise-grade AI both practical and affordable for SMEs. At a time when digital transformation seemed out of reach for many smaller businesses, Daten & Wissen positioned itself as an enabler of growth, helping organizations harness the power of data to unlock new possibilities.
With a strong focus on delivering customized AI solutions, the company has steadily carved its niche in diverse sectors including healthcare, manufacturing, finance, and retail. By blending technical expertise with deep business understanding, Daten & Wissen empowers SMEs to solve real-world problems, from streamlining operations to enhancing decision-making with predictive intelligence. Their solutions are not just about technology but about ensuring accessibility, scalability, and measurable impact for businesses that often lack enterprise-level resources.
The founders believe that democratizing AI will transform the way SMEs compete in global markets, making innovation an achievable reality rather than a distant dream. As they continue to expand their footprint, Daten & Wissen stands as a testament to how passion and purpose can reshape industries.
In excerpts from an interview conducted by Small Enterprise India, co-founders Chirag and Jitendra shared their belief that AI must be human-centered, transparent, and collaborative, embedding values like integrity, innovation, and trust at the heart of their culture.
Q) Can you tell us about the origin of Daten & Wissen? What inspired you and your co-founder to start this AI venture?
Daten & Wissen was founded in November 2019 by both of us, Chirag Tank and Jitendra Purohit, to make enterprise-grade AI practical and affordable for SMEs. We saw repeated operational gaps, manual monitoring, under-utilized camera investments, and slow, costly modernization cycles, and believed a plug-and-play, edge-first AI platform could deliver immediate safety, security, and productivity benefits without rip-and-replace projects. Our mission is to democratize AI so non-technical teams can get narrative insights, real-time alerts, and automated workflows from their existing infrastructure. We are DPIIT-recognized and an NVIDIA Inception partner.
Q) What were the initial challenges you faced as a very early-stage startup—and how did you navigate them successfully?
The main early challenges were: (1) building trust with conservative SME buyers, (2) integrating with widely varying legacy cameras and VMS setups, and (3) proving measurable ROI quickly. We responded by offering short, low-cost pilots on customers’ existing cameras, prioritizing rapid time-to-value and clear KPIs (PPE compliance, product-count accuracy, downtime). Quick wins from pilots and on-site training converted pilots into paid deployments. Being fully bootstrapped forced discipline in prioritizing revenue-driven features and direct customer support.
Q) Which specific AI and ML solutions does Daten & Wissen offer to SMEs, and how do they help enhance productivity or safety?
Our modular, plug-and-play offerings include:
- NWarch AI (video analytics): Edge-first detection — PPE/hard-hat, falls, zone intrusions, forklift collisions, unattended objects, product counting, occupancy — delivers real-time safety alerts and process compliance.
- AI Agents (LLM layer): Natural-language queries over live video, sensors, and databases — generates narrative summaries, charts, and CSV exports on demand.
- Zero-code Automation Workflows: “If-this-then-that” builder to automate alerts, escalations, and report distribution (Slack, SMS, email).
- Intelligent Document Processing / OCR: Automates invoices, POs, and other documents, reducing manual reconciliation.
- Forecasting & Predictive Analytics: Demand forecasting and predictive maintenance to reduce stockouts and unplanned downtime.
- Vehicle & Asset Tracking: Fleet and warehouse flow optimization.
Each solution is designed to reuse existing cameras and infrastructure, lowering TCO while delivering measurable safety and productivity improvements.
Q) Could you share a compelling case study where your AI video analytics (PPE detection, product counting, etc.) solved a real problem for an SME?
- Client: Mid-size manufacturing plant (anonymous on request)
- Problem: Low PPE compliance and frequent mismatch in packing counts caused safety risks, downtime, and inventory reconciliation overhead.
- Solution: Deployed NWarch AI on the client’s existing CCTV to monitor PPE compliance and automate product counting on the packaging line. Alerts were integrated into the operations dashboard and on-call workflows; weekly automated compliance reports were generated and distributed.
- Outcome: Within six weeks, PPE compliance improved from ~60% to 94%, product counting accuracy reached 99.2%, and reconciliation time fell by ~70%. An automated alert also helped avoid a potential safety incident. The pilot’s clear KPIs led to a multi-site roll-out.
Q) Which solution segment has seen the strongest traction among SMEs so far?
NWarch AI (video analytics) shows the strongest traction — particularly in manufacturing and construction/EPC, where safety and process monitoring deliver immediate ROI. We’re also seeing growing demand for Intelligent Document Processing and forecasting in mid-sized enterprises.
Q) How do you ensure the AI solutions are accessible and cost-effective for resource-constrained SMEs—especially those adopting AI for the first time?
We lower adoption friction by reusing existing cameras (no rip-and-replace), deploying edge-first models on lightweight GPU appliances or smart cameras to avoid ongoing cloud costs, offering pay-as-you-go pilots, and providing a zero-code workflow builder so non-technical staff can operate and tune automations. Short pilots, transparent pricing, rapid training, and a modular roll-out path (start with one use case → scale) keep upfront costs low and speed ROI.
Q) What has been your experience participating in SME-StartX Bengaluru? How valuable were the curated One-to-One meetings with SME manufacturers?
SME-StartX provided excellent customer access and actionable feedback. The one-to-one meetings connected us directly with SMEs that could run pilots immediately; many appreciated our camera-reuse approach and asked for turnkey pilot kits. Those conversations reinforced demand for short PoC timelines and simple onboarding, and produced several pilot commitments.
Q) Any memorable feedback or outcome from those meetings that helped refine your product-market fit?
A recurring piece of feedback was: “We want measurable outcomes in weeks, not months.” That led us to create a one-week pilot kit, pre-trained vertical templates, guided onboarding, and lighter pricing tiers for smaller sites, changes that shortened sales cycles and improved conversion rates.
Q) Looking ahead, what do you see as the biggest growth opportunity or next frontier for Daten & Wissen within India’s SME sector?
The biggest near-term opportunity is scaling VisionOS — our AI marketplace — so SMEs and integrators can discover and deploy vertical-specific plugins in a click. Construction/EPC and mid-tier manufacturing will remain high growth because of regulatory pressure and high camera density. International expansion (Europe, UAE, USA) via system integrator partnerships and localised modules (GDPR-compliant workflows, multilingual UIs) is the strategic next frontier.
Q) What advice would you give to other AI-focused startups aiming to support SME digitization while building a sustainable, impact-driven business?
Start with one clear, measurable use case and a short pilot that proves ROI. Prioritise integrations with existing infrastructure, keep pricing and onboarding simple, and focus on operator enablement, non-technical staff must be able to run and trust your solution. Build partnerships (system integrators, camera vendors) early to shorten sales cycles.
