Real Results
Across Industries

Poland · Ingredients & additives distribution

Challenge: Ingredient sourcing is research-heavy. Answering a customer brief required searching across supplier websites, technical data sheets, certificates, and SharePoint folders to find candidates with the right specification, certification, and origin. Comparable product data was scattered and buried in long PDFs — slowing matching requests and creating dependency on individual specialists' expertise.

Solution: Omniviser delivered a phased AI platform combining a matching engine that scrapes and indexes external product data, Omniviser Chat over the company's internal document repository for natural-language queries, and integration with the ERP system for a unified, current data picture. The next phase extends the matching engine into business-prospect discovery and CRM-connected outbound sales.

United States · Freight brokerage & managed transportation

Challenge: Brokers spent most of each day on repetitive rate quoting and manual double entry between the TMS and the load board. Accurate quotes required reconciling live market signals against internal lane history — a process that didn't scale, introduced pricing inconsistency, and absorbed the best people in low-leverage work instead of carrier relationships.

Solution: Omniviser implemented an AI agent platform tightly integrated with the TMS and load board that automates the rate-quoting and load-coverage workflow end to end — ingesting loads, generating priced quotes from lane history and live market data, posting to the load board, and writing negotiated rates back to the TMS. A human-in-the-loop step is preserved for edge cases and low-confidence quotes.

Poland · Dietary supplements & medicinal products

Challenge: As the company grew and data sources multiplied, key information was scattered across internal reports, external databases, and industry systems. Management and department heads relied on manual collection, reconciliation, and reporting — a process that was slow, inconsistent, and limited access to real-time indicators needed for business decisions.

Solution: Omniviser deployed an AI assistant built on a unified data model integrating selected internal and external sources. Management and department heads can now ask questions in natural language and automatically generate operational and strategic reports — with role-based access ensuring secure, appropriate visibility across the organisation.

International · Physical retail network & distributed marketing

Challenge: The company relied heavily on mass distribution of promotional leaflets and campaigns sent to broad customer groups on a weekly or bi-weekly cadence — without precise targeting. Many customers receiving promotions did not visit stores, campaign timing and frequency were inconsistent across segments, and marketing efforts were costly. The organisation lacked the ability to segment customers effectively or optimise outreach based on actual engagement and purchasing patterns.

Solution: Omniviser implemented a machine learning–based solution to analyse customer behaviour and optimise marketing distribution. It integrated data from sales transactions, loyalty programmes, and campaign history into a unified view of customer activity. ML models identify patterns and predict responsiveness, enabling smarter targeting based on customer segments and behavioural signals — including "digital twin" profiles used to simulate and optimise marketing strategies.