Legal AI

Deeligence

Est. 2022 Australia Updated 2026-03-19
Unverified by r/legaltech members — this page is based on publicly available information, not hands-on testing or practitioner feedback. Verify your experience with Deeligence

Deeligence is an Australian-founded due-diligence workflow platform for transactional lawyers and deal teams. It sits between the data room and the final client report: teams assign review work, track changing uploads across Ansarada/Intralinks/Datasite/Google Drive/SharePoint, run AI contract screening and clause summaries, and export client-ready Word reports in house style. Public evidence is still heavily vendor-authored, but the case studies are more concrete than most early-stage legal-AI vendors: Mayne Wetherell reports 75+ lawyer hours saved on one large transaction and says the firm decided it will not run transactions without the tool; HopgoodGanim says lawyers completed reviews up to 83% faster and only needed 20 minutes of training; Cowell Clarke reports ~70+ hours saved on an average diligence and 92.5% AI accuracy before lawyer review; GrilloHiggins reports 15+ hours saved on an average diligence plus live in-scope indexing on changing Google Drive matters. Founded in 2022 by Elena Tsalanidis and Justin Hansky. Public press confirms an AUD $1M pre-seed round in April 2024, while the vendor stub and TLTF data indicate roughly $1.7M total funding. Pricing is not public: the vendor offers a pilot with core features and personalised support, then moves buyers onto subscription plans discussed in demo. Security claims mention ISO 27001 compliance, encryption, MFA, and regular security audits, but no public SOC 2 report, SSO/SAML detail, security whitepaper, DPA, or data-residency documentation was surfaced.

Company Info

  • Founded: 2022
  • Team size: 1-10 employees
  • Funding: $1.7M
  • HQ: Canada
  • Sector: In-House Automation

What We Haven’t Verified

This page was assembled from publicly available information. Feature claims and workflow mappings are based on what the vendor and third-party listings publish — not hands-on testing or practitioner feedback.

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