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Automated reviews rapidly identify unconformities, missing or handwritten values, and other deviations delivering 60-80% reduction in review time while increasing detection speed and reliability.
Team collaboration is fostered by the ability to comment, tag and highlight deviations directly in the document so that deviation investigation time can be cut significantly.
Turning PDF documents into machine-readable data enables organizations run analytics and implement targeted corrective actions, resulting in improved batch yield and overall product quality.
Feed batch record documents into a flexible workflow
Let the algorithms run compliance checks such as signature, values and process steps
Set up instant alerts with your own trigger
Review all non-conformities in the documents and tag colleagues
Get draft deviation forms and summaries ready to share
Get the whole content in structured data form for further analysis and LLM processing
The trained algorithms understand the instructions and check all the values and steps. Values out of range, missing steps or handwritten annotations are flagged in an issue list, ready for processing.
Add your own customizable checks
Besides standard checks, create business rules and alerts specific to your requirement and internal language.
Trigger collaboration with colleagues directly in the document in 2 clicks. In case of deviations, get a draft deviation form. To run the investigation, use smart search to locate information in the current and previous batches.
And when the review is ready, get a summary of the information to share to stakeholders. A standardised output that feed into your PQRs.
Each time your batch record documents are processed, a digital twin in structured xml format is created including all the table values, with their context and metadata. This enables further analyses to spot correlations and create new insights leading to less deviations and improved yields.
GxP compliance by design, providing full traceabiity, auditability and replicability
Highest accuracy for complex documents, through document & table specific models
Models are fine-tuned on your data for precision and privacy. Your models, your data.
Human-in-the-loop interfaces to ensure validity and compliance of data and models
Traceability back to the source, for auditing and versioning, and avoiding the risk of hallucination
1/ Initial feasibility and scoping: 3 weeks
2/ Implement the first solution: 1 month
3/ Improve the solution: 2 months
4/ Roll out across products: 6 months
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Download the PDF case study to see how we implemented smart automation on the Batch Records of a large Pharmaceutical company
EBR is a huge investment and may not even be possible in certain facilities
Given GMP requirements, full automation systems are not allowed
Standard solutions don't work in our processes
Our data and processes are too sensitive to be shared.
Smart automation is based on your current documents
Tasks are automated but humans keep full control of the final outputs
Models train on your data for accuracy and apply your own instructions
Models dedicated to you run in your own instance. Nothing is shared.
