Helping users search, manage, and retrieve the desired data efficiently.

40K

Contracts approx per enterprise,

Image showing how contract data are hidden and hard to search and find

Contract data are layered and scattered. Creates operational inefficiencies and risk exposure.

Contract Data is Huge

Contract data exists in huge volumes—unstructured and hard to navigate. For legal users, this means time lost, context missed, and constant friction. This complexity is exactly what sets the stage for a better, more intuitive way to interact with the data

A contract connects to various documents, each containing multiple clauses and metadata such as expiration dates, party names, and additional details.

Data and Connections

Say a user needs to find all contracts with a limitation of liability clause that expire on 12 Oct 2028. That one question requires tracing connections across enterprises, contracts, documents, clauses, and metadata.

Search Bar with text Show all contract's expiring of 12 October with limitation of liability

IACCM reports that a typical business with 1,000 employees wastes $2.5 million to $3.5 million each year just searching for and recreating lost documents. That’s money slipping away simply because contract data is locked in systems that make access difficult.

90% of contracting professionals say finding specific documents is a challenge.

The current experience.

01

Pre Search

The user must locate and articulate the sequence to start the search quickly. The user will look for the search bar.

03

Search Result & Filter

Views results and applies filters for further refinement

02

Entering the Query

The user types a query using basic keywords or entity IDs.

04

Insight & Action

The user reviews filtered results, extracts insights, and makes decisions.

The Video Below Explains this Above Journey with Existing Screens

Introduction of GenAI

Integrating GenAI into the Sirion ecosystem has transformed the search experience by addressing longstanding pain points and significantly enhancing user efficiency across the journey.

Together, these capabilities empower users to find what they need faster, with greater clarity and confidence, making every interaction smarter and more efficient

Natural Language Processing

Enables users to interact using everyday language, making it easy to express complex search queries without needing technical phrasing or structured inputs

Seamless User Journey

Delivers a fluid experience by minimizing context switching, allowing users to move effortlessly between tasks and maintain focus throughout their workflow.

Context Retention & Intelligent Filtering

Maintains conversation history and intelligently filters results based on user intent, ensuring relevant and precise outputs even in complex, multi-turn queries

Realtime Data Visuals & Actionable Suggestions

Presents key insights through intuitive visuals and clear recommendations, helping users quickly understand metrics and take informed actions with confidence.

My UX Approach: Making Search Feel Like Thought

When I examined user behavior, I noticed something subtle: people weren’t really searching. They were voicing half-formed ideas — almost thinking out loud. Traditional filters and keyword search didn’t match that mental process.

So I reframed the problem:What if users could just ask — and the system understood the intent, retained the context, and served the answer?

That’s why I called it Thought. Unlike search, which matches keywords, Thought mirrors cognition:

Captures messy intent instead of requiring polished queries.
Retains context, like memory in a real conversation.
Responds visually and naturally, so answers feel immediate and human.

This shaped the foundation of AI-powered conversational search — where users type naturally (“Show me all Vodafone contracts with COLA clause”), the system understands nuance, remembers context, and responds in ways that reduce back-and-forth.

But here’s where Thought goes beyond tools like ChatGPT:

Domain-specific intelligence → It’s grounded in contracts and clauses, so answers are precise and trustworthy.
Visual + conversational hybrid → Results aren’t just text; they become clause explorers, dashboards, and summaries that lawyers can act on.
Task-oriented memory → It remembers context across workflows (“the NDA I asked about earlier”), not just within a single chat.
Explainability → Every answer shows why (the exact clause, rule, or data source), building trust in high-stakes legal work.

In short, Thought isn’t just about delivering answers — it’s about delivering trusted, actionable insights in the way professionals actually think and work.

UX Enhancements That Shaped the Experience

To translate this vision into practice, I designed key UX enhancements:

1. Reworking the Mental Model of Search

Shifted from rigid, field-by-field filtering to natural, question-driven input.
Supported fuzzy, incomplete, and contextual prompts, so half-formed ideas still worked.
Built fallback UX for vague queries — instead of “no results,” the system suggested refinements.
Made chat context visible, so users always understood where they were in the flow.

2. Bringing Clarity to Data and Insights

Created response pages that combined summaries, filters, and metadata cards — like a structured search landing page.
Added inline interpretation panels so users could see what the system “understood” from their query.
Used color-coded visualizations to highlight risk patterns, clause distributions, and anomalies at a glance.

3. Designing for Transparency and Trust

Paired every AI answer with an explanation of logic (e.g., “COLA found under description X”).
Allowed users to inspect and adjust underlying filters to refine results with confidence.
Ensured the system was never a black box — trust was built into the design.

Landing Page AI Search

AI Search with a chain of reasoning for better trust and transparency.

The Response Page

The Search Response Page Layout with Description of design desicions.

Result and Data Filtering

But, to get the desired result needs a deterministic experience in the list view

Two circle intersecting to show how search and listing ecosystem overlaps.

A streamlined listing page enhances scan ability, reduces friction, and helps users find what they need faster.

Current Listing Page

Listing page current design with pain points.