SciJustice. Bringing safe, structured expert consultation into judicial workflows.
Many legal decisions need domain experts. Courts often need specialists to support complex cases. SciJustice modernises this through a secure digital platform built on four design goals: faster expert matching, compliance at every step, secure communication, and efficient management across multiple active cases.
At-a-glance overview + clear next best action
Natural-language intake the AI can later structure
Field, subfield and time-commitment filters
Boundaries reviewed before any request goes out
AI summarises the inputs into a structured request profile
Match scores explain why each expert was recommended
Affidavit-gated session before any chat begins
Pending requests, ongoing chats and summary tasks in one view
Conflict-of-interest reminder, request details, accept / reject / hold
The context.
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Many legal decisions require domain experts.
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Courts often need specialists such as doctors, engineers, financial analysts or forensic professionals to support complex cases.
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SciJustice was designed to modernize this process through a secure, transparent digital platform.
What we set out to achieve.
Faster Expert Matching
Help judges find the right expert quickly — match score, credentials and availability surfaced together.
Compliance
Ensure compliance at every step with built-in safeguards and explicit checkpoints before sensitive actions.
Secure Communication
Enable trusted conversations and document exchange inside affidavit-gated sessions.
Efficient Management
Simplify coordination across multiple active cases with clear status and a single dashboard.
How I worked through it.
Dashboard for the judge
An at-a-glance overview of ongoing requests, completed consultations and expert activity. Designed to reduce cognitive load, prioritising the next best action — start a new expert request — over information density.
Guided request creation
A 4-step wizard: inquiry details (natural-language intake the AI later structures), expertise selection (field, subfield, time commitment), compliance checkpoint, and a review screen with an AI summary the judge can edit before submitting.
Expert discovery & selection
Match results explain why each expert was recommended — match score, credentials, availability — instead of dumping random profiles. CV details open in a focused modal so judges can validate experience without losing context.
Secure communication & finalisation
Locked sessions with required affidavits before chat begins, a structured consultation chat that reinforces boundaries around case-specific information, and a session summary with downloadable records to create a reliable audit trail.
The outcome.
What I’d carry into the next one.
In high-stakes systems, clarity isn’t a convenience — it’s essential.
Trust signals (status, compliance, attribution) are first-class UI, not microcopy.
Step-based wizards beat single long forms when the cost of a wrong submission is high.