Case study·Platform

Source-linked evidence review

From answers without sources — to a reviewed evidence trail behind every claim

96%
Source-trace coverageEvery claim linked back to a document, page and paragraph
“I could see why it said something before deciding whether to trust it.”
Professional Reviewer · Professional services review pilot
Professional services / regulated operations·10-person review pilot covering ~80 source-linked answers per week across SharePoint, Drive, parsed PDFs and a CRM·4-week pilot·United Kingdom
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01Pilot envelope
Pilot length4 weeks
First signal3 days
First ROI28 days
Team alongside4 seats · 2 colleagues

4-week trust pilot; every answer required provenance; corrections were captured as reusable guidance.

02What it owns
Reports toOperations Lead, dotted line to the data owner on extraction guidance changes.
Owns
  • Evidence panel — each answer paired with the source paragraph and a working link to the document in SharePoint, Drive or the parsed PDF
  • Source-trace coverage — every claim labelled with the document, page and paragraph that produced it
  • Correction log — reviewer fixes captured with a reason code, attributed by reviewer and surfaced to the data owner
  • Confidence thresholds — current bands surfaced beside each answer so reviewers can apply the agreed policy in place
  • Reusable guidance — promoted corrections fed back into the extraction rules across SharePoint, Drive, PDFs, Word, Excel and the CRM
Does not do
  • Auto-acceptance of low-confidence answers — every flagged item waits for a named reviewer
  • Confidence band changes — surfaces the current policy, does not change thresholds without governance sign-off
  • CRM writebacks — proposes updates to CRM records; nothing is written until a reviewer approves
Done looks like

Reviewers open an answer, see the source paragraph beside it, and either approve or correct in place. Every correction is captured, attributed and folded into the next week's guidance.

03The team
AI teammates2
NoahSurfaces the source paragraph behind every answer, with a working link back to the document in SharePoint, Drive or the parsed PDF, and the page reference next to each value.
IrisCaptures every reviewer correction with a reason code, logs it to the audit trail and proposes the fix back to the extraction guidance for the data owner to promote.
Human team4
  • Operations LeadOperations
  • 7 Professional reviewersReview
  • Data OwnerGovernance
  • AdministratorSystems
04Connected stack
SharePointGoogle DriveAdobe AcrobatWordExcelCRMUnify console
05What it returned
96%Source-trace coverageEvery claim linked back to a document, page and paragraph
38%Reviewer correction time reductionAgainst the baseline review sample
SignedConfidence threshold policy agreedFirst version approved by the data owner and operations lead
  • Day 0
    Co-ordinator sessionOperations Lead, reviewers, data owner and administrator agree the review surface, confidence bands and the first set of answerable questions.
  • Day 3
    First evidence panelNoah surfaces source paragraphs beside the first set of answers drawn from SharePoint, Drive and Adobe-parsed PDFs.
  • Day 10
    Read-only review liveReviewers work through a quarantined answer queue; every claim carries a paragraph-level link and a confidence band, with no writes anywhere yet.
  • Day 18
    Corrections wired inIris captures reviewer fixes with reason codes; the first batch of guidance changes is proposed to the data owner.
  • Day 24
    Threshold policy agreedOperations Lead and data owner sign off the first confidence threshold policy; corrections begin informing the extraction rules across SharePoint, Drive and the CRM.
  • Day 28
    ROI reviewSponsor signs off on three baseline metrics and approves expansion to a second review surface inside the same team.
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