Zenoqar gives your team a single source of truth for vehicle specifications, pricing, and competitive positioning — verified daily by dedicated researchers, ready for analysis in seconds.
Automotive pricing and product planning teams rely on fragmented data — scattered PDFs, outdated spreadsheets, and manual research that's stale before it's shared. Decisions that should take minutes take days.
Zenoqar is a B2B analytics platform purpose-built for automotive markets. Dedicated researchers maintain a living database of vehicle specifications. Analysts query, compare, and report on that data through a modern web interface — no exports, no reconciliation, no guesswork.
Vehicle data is extracted, normalised, and cross-checked by an AI pipeline, then gated by SME review before it ships. Every field carries its source and verification status — built from the start to feed AI applications, not just dashboards.
Build workspaces of vehicles that matter to you. Set a benchmark. See differences at a glance — across trims, across brands, across model years.
Value Analysis scores competitors against your benchmark. Price History tracks pricing across generations. Ladder charts reveal positioning gaps on any two parameters.
A pipeline of specialized agents does the heavy lifting. Humans sign off on every output.
Keeping every vehicle current — ~800 parameters, daily, within 48 hours of every OEM update — is impossible by hand. Instead, our pipeline of specialized AI agents handles the heavy lifting: classifying manufacturer documents, discovering new models and trims, extracting structured specifications, and cross-checking values against peers in the database.
Every output passes through a human researcher before it reaches your workspace. The result is the speed of automation with the accuracy of expert review — and a system that gets faster and more accurate every quarter as the agents learn.
Agents scan manufacturer sources and flag new models, trims, and updates.
Structured specifications pulled from PDFs, web pages, and price lists.
Every value cross-checked against peer vehicles and historical snapshots.
A trained researcher reviews and signs off before publication.
Automated discovery, extraction, cross-checking, and validation.
Every published record is signed off by a researcher.
The pipeline runs end-to-end every business day.
Every vehicle is a version (engine + trim + body + market). Every price or spec change creates a new instance — a time-stamped snapshot.
Search across makes, models, body types, or any specification parameter. Use operators like equals, range, includes, and null checks. Combine criteria to find exactly the vehicles you need.
Save search results into named workspaces. Compare vehicles side-by-side — all parameters or differences only. Set any vehicle as the benchmark and see how others stack up.
An AI pipeline pulls data from OEM sources, normalises it across markets, and routes every change through SME approval. You get a workspace with the data already structured, verified, and ready to analyse — with role-based access so your team sees only what they need.
Every report runs over your workspace, respects your benchmark, and regenerates as data updates.
Zenoqar is an automotive market intelligence platform founded in 2026. We're rebuilding the spec-data stack on AI-native infrastructure with SME-gated quality control — expanding by anchor-client commitment.
Our customers are product, pricing, and competitive teams at OEMs, leasing providers, and dealer groups who need fast, defensible answers instead of stale PDFs and patched-together spreadsheets. We built Zenoqar because every one of us has felt that pain firsthand.