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Advanced Search Solution

Advanced Search that Accelerates Document Analysis and Reduces Legal Costs

client

Melior AI

company

UserActive

category

Legal SaaS

team

Lead designer, developers and stakeholders

role

Product designer

Intro

Melior AI Contract Intelligence makes it easy to deal with third-party paper: to classify, understand, and navigate business documents, automate workflows, and manage your contracts with ease.

Intro

Melior AI Contract Intelligence makes it easy to deal with third-party paper: to classify, understand, and navigate business documents, automate workflows, and manage your contracts with ease.

Problem

Melior AI's platform was created to handle large volumes of third-party documents, but clients struggled with efficiently analyzing these documents. Legal teams often had to manually review extensive contracts to extract important data, resulting in a slow and costly process.

Problem

Process

To address the challenge, we followed a structured user-centered design process:

Conducted interviews with Melior AI stakeholders and legal teams to identify key pain points and define core requirements for advanced search.
Designed a clear structure for document organization and user flows to integrate advanced search seamlessly into the platform.
Developed low-fidelity wireframes and interactive prototypes, focusing on document filtering, keyword search, and contextual relevance.
Gathered feedback from stakeholders, refining the design for improved usability and responsive performance.
Worked closely with engineering teams to ensure a smooth handoff, providing design documentation.

To address the challenge, we followed a structured user-centered design process:

Conducted interviews with Melior AI stakeholders and legal teams to identify key pain points and define core requirements for advanced search.
Designed a clear structure for document organization and user flows to integrate advanced search seamlessly into the platform.
Developed low-fidelity wireframes and interactive prototypes, focusing on document filtering, keyword search, and contextual relevance.
Gathered feedback from stakeholders, refining the design for improved usability and responsive performance.
Worked closely with engineering teams to ensure a smooth handoff, providing design documentation.

To address the challenge, we followed a structured user-centered design process:

Conducted interviews with Melior AI stakeholders and legal teams to identify key pain points and define core requirements for advanced search.
Designed a clear structure for document organization and user flows to integrate advanced search seamlessly into the platform.
Developed low-fidelity wireframes and interactive prototypes, focusing on document filtering, keyword search, and contextual relevance.
Gathered feedback from stakeholders, refining the design for improved usability and responsive performance.
Worked closely with engineering teams to ensure a smooth handoff, providing design documentation.

Impact

Enabled legal researchers to query thousands of documents more efficiently by designing a smarter, more approachable search experience, leading to faster discovery, fewer failed queries, and improved retention of power users.

Process

To address the challenge, we followed a structured user-centered design process:

Conducted interviews with Melior AI stakeholders and legal teams to identify key pain points and define core requirements for advanced search.
Designed a clear structure for document organization and user flows to integrate advanced search seamlessly into the platform.
Developed low-fidelity wireframes and interactive prototypes, focusing on document filtering, keyword search, and contextual relevance.
Gathered feedback from stakeholders, refining the design for improved usability and responsive performance.
Worked closely with engineering teams to ensure a smooth handoff, providing design documentation.

Solution

The key features of the solution included:

Intelligent Filtering:
Users can filter documents by various parameters, such as contract type, date, parties involved, and specific clauses. This reduced the time spent manually sorting through documents and allowed for a more targeted search.
Contextual Keyword Search:
Advanced search enabled the identification of relevant keywords within contracts and highlighted key clauses. The context around keywords was presented to help users quickly understand the relevance of a search result.

The key features of the solution included:

Intelligent Filtering:
Users can filter documents by various parameters, such as contract type, date, parties involved, and specific clauses. This reduced the time spent manually sorting through documents and allowed for a more targeted search.
Contextual Keyword Search:
Advanced search enabled the identification of relevant keywords within contracts and highlighted key clauses. The context around keywords was presented to help users quickly understand the relevance of a search result.

The key features of the solution included:

Intelligent Filtering:
Users can filter documents by various parameters, such as contract type, date, parties involved, and specific clauses. This reduced the time spent manually sorting through documents and allowed for a more targeted search.
Contextual Keyword Search:
Advanced search enabled the identification of relevant keywords within contracts and highlighted key clauses. The context around keywords was presented to help users quickly understand the relevance of a search result.

Solution

The key features of the solution included:

Intelligent Filtering:
Users can filter documents by various parameters, such as contract type, date, parties involved, and specific clauses. This reduced the time spent manually sorting through documents and allowed for a more targeted search.
Contextual Keyword Search:
Advanced search enabled the identification of relevant keywords within contracts and highlighted key clauses. The context around keywords was presented to help users quickly understand the relevance of a search result.

Impact