GageList launches Clarity AI to automate calibration certificate entry

GageList on Aug. 19 launched Clarity AI, a new feature that reads emailed or uploaded calibration certificates and drafts gage records for human approval. The company says the tool can cut processing time from minutes to seconds while keeping a person in the review loop for every record.

Why it matters: - Calibration teams often spend hours manually typing certificate data into quality systems after a gage returns from calibration. - GageList is targeting that bottleneck with AI that speeds up processing without removing human approval from the workflow. - The company says the result is less manual work, fewer data-entry errors and faster updates to due dates and records.

What happened: - GageList launched Clarity AI, a new feature for its cloud-based calibration management platform. - Clarity AI was previewed at the NCSLI Workshop & Symposium and officially launched in a live webinar on Aug. 19. - The feature reads incoming calibration certificates and drafts gage records for review before a person approves them.

The details: - Calibration labs can email certificates to a private, whitelisted inbox, or users can upload files in bulk. - Clarity AI reads each certificate, matches it to the correct gage and stages a draft record. - A team member reviews the extracted data next to the original document, edits as needed and approves the record. - One approval creates the record, updates due dates and attaches the certificate with a full audit trail. - In internal testing on 643 real-world calibration certificates, Clarity AI cut processing time from 8 to 10 minutes to seconds per certificate. - GageList estimated that improvement as an up to 98% reduction. - The feature handles PDF, JPEG and PNG files from any lab in almost any layout or language. - Clarity AI can process fully handwritten documents, mixed handwritten-and-printed pages and multi-page certificates. - The software distinguishes a gage's due date from the due dates of calibration standards listed on the same page. - Users can configure the feature per account, choose which fields to extract and tune prompts to fit internal requirements. - Users can combine multiple data points, such as temperature, humidity and pressure, into a single custom field. - Clarity AI runs in a closed, private environment on Microsoft Azure AI. - Certificate data is processed privately, not used to train AI models and not shared with outside parties. - GageList is independently audited to SOC 2 Type II. - Clarity AI is included in GageList's Plus, Pro, Max and Multi-Site plans. - Those plans include 100 pages of certificate processing per month, with additional usage priced on consumption. - GageList says the feature is the first calibration management platform to read incoming calibration certificates with AI and draft gage records for human review.

Between the lines: - The launch reflects a broader push to use AI for document extraction in regulated workflows, where speed matters but so does traceability. - GageList is keeping a person in the loop, which should help address quality-system concerns about automated decisions. - The focus on private processing and audit trails signals that data security and compliance are central to the product pitch, not afterthoughts.

What's next: - GageList plans direct API intake from calibration labs. - The roadmap includes support for the emerging digital calibration certificate, or DCC, standard. - The company also plans a future capability that would evaluate certificates against ISO/IEC 17025 and user-defined criteria, flagging missing content or out-of-range results before an auditor finds them. - GageList says future updates may help surface issues earlier in the quality process.

The bottom line: - Clarity AI turns a slow, manual calibration workflow into a mostly automated review process, while keeping final approval in human hands.