Modliq is built by Qeltrava AI to help manufacturing teams turn production data into optimized decisions, validated quality, and buyer-ready proof.
Modliq is a product by Qeltrava AI, an AI-focused company building practical, industry-ready AI systems from Tamil Nadu, India. With Modliq, Qeltrava AI is focused on helping manufacturers turn production data into better process decisions, quality evidence, and buyer-ready reports.
Many factories still rely on spreadsheets, manual reports, and disconnected tools to make critical production and quality decisions. Modliq was created by Qeltrava AI to help manufacturers use their existing data to improve process decisions, reduce quality losses, and present stronger evidence to buyers and auditors.
AI-assisted recommendations for process improvement
Buyer-ready Quality Passports with full traceability
Free launch pilot & transparent plant pricing
Tamil Nadu is home to automotive, textile, engineering, chemical, electronics, and food manufacturing clusters. Modliq is built with this manufacturing-first mindset.
Modliq is built from Tamil Nadu by Qeltrava AI for the manufacturing world. We understand the realities of Indian factory floors, export supply chains, and MSME operations.
Small and medium enterprises that need affordable, practical tools for data-driven decisions.
Owners who want to see yield, quality, and efficiency improvements without expensive consultants.
Leaders who need SPC, Cp/Cpk, and audit-ready evidence at their fingertips.
Companies that need buyer-ready Quality Passports and traceability for global customers.
Suppliers who must demonstrate quality discipline and process capability to their customers.
Engineers who want AI-assisted recommendations validated through controlled trials.
We start with the simplest solution that works. Complexity is added only when necessary.
Every claim is backed by data. We show you the numbers, not the marketing.
AI suggests, engineers decide. Humans remain in the loop for every critical decision.
All AI recommendations should be validated through controlled trials and responsible engineering review.
We design for the realities of Indian factory floors — intermittent connectivity, mixed data formats, and varied skill levels.