CROs often face time-draining complexity when sponsor-supplied clinical trial data arrives in inconsistent formats. Our AI-powered service harmonizes this data rapidly helping clinical operations and data teams accelerate study start-up and reduce rework.
Sponsor data rarely arrives ready-to-use. CROs receive diverse file formats from sponsors and third-party data providers such as central labs, ePRO vendors, and imaging partners. These files often include
Even across studies from the same sponsor, CROs deal with
These issues introduce delays, increase quality risks, and consume valuable operational bandwidth.
This solution is designed for CROs who need to streamline study startup, reduce manual reconciliation, and improve data readiness for both internal and sponsor-facing teams. It brings measurable efficiency to areas where delays and friction are most common.
We apply domain-aware AI parsing, structure recognition, and rules-driven transformation to
Auto-extract and validate tabular fields, column headers, and values across Excel, CSV, XML, and PDF
Normalize inconsistent field names and units (e.g., HGB, Hemoglobin, HgB → Hemoglobin (g/dL))
Validate field mappings and flag schema drift
Output analysis-ready files in your required format (e.g., SDTM-like, for internal dashboards, or downstream EDC load)
All without needing fixed templates, macros, or pre-written conversion rules.
This frees up your team to focus on strategy and quality — not formatting fixes.
Let’s discuss how this might help your team reduce delays, streamline data readiness, and simplify sponsor collaboration.
