Structured plate recognition output
Parkese’s ALPR endpoint parses a vehicle image and returns the plate number, state, RTO, series, number, confidence, and script type in structured JSON.
Parkese is a parking management and ALPR platform for vehicle recognition, access passes, pricing control, and reporting, with a REST API.
Parkese is a parking operations and vehicle-recognition platform with two visible product areas on the site: a parking management suite and an ALPR API. The ALPR page focuses on license plate recognition for Indian roads, while the pricing page shows plans for employee access passes, visitor parking, and a combined setup.
For ALPR, Parkese accepts a vehicle image through a REST API and returns parsed plate data such as state, RTO, series, number, validity, confidence, and script type. The page positions it for real-time use in parking, toll, and access-control systems, with support for Roman and Devanagari scripts and structured JSON responses that are easy to store or automate against.
The parking product side is organized around access passes, parking control, dynamic pricing, multi-location dashboards, live reports, and attendant management. The pricing page also shows a 15-day free trial and separate plan options for access, parking, or both, suggesting the platform is designed for operators who want one system to manage entry, pricing, and reporting.
Parkese’s ALPR endpoint parses a vehicle image and returns the plate number, state, RTO, series, number, confidence, and script type in structured JSON.
The ALPR page says the system works with Roman and Devanagari script plates and can transliterate Devanagari text into a Romanized result.
The API is described as handling noisy, angled, and shadowed images without preprocessing, which reduces setup work for client apps and camera pipelines.
The product validates Indian plate formats, including standard, BH Series, diplomat, armed forces, and electric plates, against MoRTH rules.
The response includes scan history and searchable records by plate number, state, or date range, supporting review and audit workflows.
The pricing page presents separate plans for access management, parking management, and a combined plan, indicating support for both pass-based and parking workflows.
Use the ALPR API to identify arriving vehicles at entrances and feed the result into barrier control, entry logging, or automated fee calculation.
Apply the access-pass workflow for employees or residents who need free or monthly passes and a simpler admission process than one-off ticketing.
Use the parking-management tools for visitor lots that need dynamic pricing, attendant coordination, live reporting, and multi-location oversight.
Use scan history and searchable records when you need to review plate reads by number, state, or date range for audit or incident follow-up.
Use the ALPR API as a backend data source for parking, toll, or access-control applications that need structured plate parsing in a simple REST flow.
The source shows a contact form and an FAQ section, but it does not publish step-by-step onboarding details. Based on the product pages, Parkese is set up as a web-based parking and ALPR platform that users can start through the site’s trial or contact flow.
Parkese is presented as a parking operations platform for businesses that manage access, passes, pricing, or vehicle recognition. The ALPR page also positions it for parking, toll, and access-control systems that need fast plate parsing.
Yes. The pricing page includes an Access Plan that mentions free or monthly passes, and a 15-day free trial callout appears on the page.
The ALPR page says responses return structured JSON with fields such as plate number, state, RTO, series, number, confidence, and script type, and it shows scan history and searchable records.
The FAQ list asks about integrations, security, customization, multiple locations, attendants, and dynamic pricing, but the source text does not provide detailed answers. The ALPR page does show a REST API with API-key authentication and multipart/form-data image uploads.
Arduino VENTUNO Q is an edge AI computer for AI and robotics, combining AI inference and deterministic control on one board with Arduino App Lab support.
ByteAsk is a terminal-first AI coding agent for C and C++ that edits repos and verifies changes with compilers, debuggers, sanitizers, and tests.
CreateOS Sandbox is an isolated compute environment for running code and agent workloads in Firecracker micro-VMs with private networking and SDK, CLI, or MCP control.
hob is an independent workspace for coding agents, with local control over sessions, terminals, history, routing, and follow-up work.
Ably Chat is a chat API platform for custom realtime chat apps, with rooms, typing indicators, presence, reactions, message updates and usage-based pricing.
Manta AI is an autonomous web app testing tool that maps app behavior, catches regressions, and generates tests from a URL, no scripts or selectors needed.