Better-prepared investigation
Organise evidence and possible approaches so researchers can spend more time testing the questions that matter.
FROM POSSIBILITY TO PRACTICE
What it does for your business
For your research and development team, “Scientific data extraction” can become a repeatable workflow rather than a separate task handled from scratch each time. AI can read information from the supplied material and organise it into the fields or structure your team needs. It fits into technical investigation, literature review and experiment planning, using your business information and the standards your team already works to.
The value it could bring
These are the improvements to evaluate against your current process. We agree the scope and test the value with your team.
Less manual rekeying
Move information from source material into a usable structure with fewer repetitive read-and-copy steps.
Catch gaps before the handoff
Surface missing or uncertain information while its source is still available to the reviewer.
EVIDENCE FROM OTHER BUSINESSES
Published ROI evidence
We have not linked a comparable published financial ROI study for this use case yet. That leaves it unranked, rather than assigning an estimated score. A pilot can measure benefits and total implementation and running costs in your business.
How it works in your business
STEP 1
Bring in the right context
Select the relevant information from your research library, lab records and analysis tools. Agree what a good result looks like with your research and development team, including the rules, examples and permissions the workflow needs.
STEP 2
Turn the task into a workflow
Pull structured results out of papers and reports. The workflow identifies the required information, preserves references to its source and highlights missing or uncertain fields for review.
STEP 3
Put the result to work
Return structured information to the team's existing tools, with incomplete or uncertain items in a review queue. Researchers verify citations, calculations and methods before using a result as evidence or a scientific conclusion.
AN EXAMPLE IN PRACTICE
A member of your research and development team needs help with “Scientific data extraction”. They supply research question and relevant source literature, together with the relevant instructions and the result they need. The workflow prepares an initial result with its supporting context, flags missing information and returns it for review. The owner can correct it and use the accepted result in the team's research library, lab records and analysis tools.
Start with a focused pilot
Choose one workflow, one team and a representative set of real tasks. We establish the current baseline, build the first version and review the results together before expanding it.
What we would start with
Depending on the scope, useful inputs include:
- Research question and relevant source literature
- Approved experimental records or technical data
- Methods, assumptions and evaluation criteria
We agree access and integration with your research library, lab records and analysis tools as part of the design.
How we would measure value
- Time spent preparing each item
- Accuracy and completeness of the extracted information
- Time to a verified synthesis and reproducibility of the supporting work
Researchers verify citations, calculations and methods before using a result as evidence or a scientific conclusion.
LET’S BUILD IT TOGETHER
Could this help your business?
Tell us how your team works today and what you would like to improve. We’ll explore the opportunity, shape a practical first step and build it with you.
Talk to us about this use case