Enterprise Knowledge & Search

Organizations store valuable information across many different places - documents, support tickets, project wikis, and chat conversations. Finding the right information often requires employees to search across multiple systems and manually piece together answers.

This can lead to wasted time, missed information, delayed decisions, and answers that are difficult to verify or trust.

Build an AI-powered Knowledge & Search Agent that helps employees find and understand information from multiple organizational data sources.

The solution should allow a user to ask a business question in natural language and receive a clear, useful answer based on the organization's available information.

The answer should also show where the information came from, so users can verify the response and understand why they can trust it.

• Multi-source knowledge: Work with information from sources such as documents, support tickets, wikis, or chat conversations.
• Intelligent search: Find relevant information even when the user's question does not exactly match the wording in the source.
• Grounded answers: Generate answers based on the available organizational information rather than unsupported assumptions.
• Source attribution: Show relevant sources, citations, or links that allow users to verify the answer.
• Natural-language interaction: Enable users to ask questions conversationally and receive clear, easy-to-understand responses.

A functional prototype or agentic workflow that accepts natural language enterprise queries, retrieves answers from indexed organizational datasets, displays verifiable reasoning and sources, and presents the final answer in an intuitive, trust-building interface.

Agentic Workflow Automation

Many business processes - such as procurement approvals, insurance claims, employee onboarding, and financial reconciliation - still require employees to manually move information between different systems and perform repetitive tasks.

This can result in wasted time, errors, delayed decisions, and difficulty handling exceptions or unusual cases.

Build an AI-powered Workflow Automation Agent that can help automate a real business process across multiple systems or steps.

The solution should be able to understand the task, perform routine actions, handle common exceptions, and involve a human when a decision requires human judgment or approval.

• Multi-step automation: Automate a business process involving multiple steps, tasks, or systems.
• Intelligent task execution: Use AI to understand information and determine what action should happen next.
• Exception handling: Identify missing information, errors, unusual situations, or cases that cannot be safely automated.
• Human-in-the-loop: Escalate appropriate cases to a human with the relevant information and context needed to make a decision.
• Process visibility: Show what actions were taken, what decisions were made, and where human intervention was required.

A functional prototype or agentic workflow that executes a multi-system business process end-to-end, demonstrates real-time exception detection and handling, and features an intuitive human-in-the-loop escalation interface.

Customer & Frontline Operations

Frontline employees such as customer service representatives, field technicians, and site operators often need to find the right information quickly while helping a customer or solving an issue on site.

Important information may be spread across manuals, knowledge bases, procedures, or other systems. Searching for the right answer can take time, especially when the situation is urgent, complex, or involves a language barrier.

This can lead to longer resolution times, customer frustration, operational delays, and avoidable mistakes.

Build an AI-powered Frontline Assistance Solution that helps employees quickly understand a customer's question or operational issue and determine what to do next.

The solution should provide relevant information, guidance, troubleshooting steps, or recommendations at the moment they are needed.

• Fast access to information: Help users quickly find relevant information from manuals, knowledge bases, procedures, or other organizational sources.
• Context-aware assistance: Provide answers and recommendations based on the specific customer question, task, or situation.
• Actionable guidance: Go beyond simply answering a question by suggesting useful next steps, troubleshooting actions, or relevant procedures.
• Natural interaction: Allow users to interact using natural language, voice, text, or other appropriate interfaces.
• Inclusive support: Consider multilingual or accessibility needs where they are relevant to the chosen use case.

A functional prototype or mobile-first assistant that accepts live operational or customer queries, searches organizational knowledge sources in real time, translates inputs and outputs on the fly, and presents actionable guidance through an intuitive, low-latency interface.

Open Innovation with Gemini Enterprise

Organizations across industries face many unique challenges that may not fit into a specific business process or existing software solution.

These challenges could involve how people work, make decisions, manage information, serve customers, analyze data, or solve industry-specific problems. Generative AI creates new opportunities to rethink how these challenges are addressed.

Identify a real organizational problem or opportunity and build an AI-powered solution using Gemini Enterprise to address it.

Your solution can focus on any industry, business function, or organizational challenge, as long as you can clearly explain:

• Who the solution is for.
• What problem it solves.
• How the problem is currently being addressed.
• How your AI solution improves or transforms the existing approach.
• What measurable value the solution could create.

• Meaningful Gemini Enterprise usage: Use Gemini Enterprise as an important part of solving the chosen problem.
• Clear problem-solution fit: Address a specific and meaningful organizational need rather than creating a generic AI application.
• Real-world context: Use relevant business information, data, workflows, or processes where appropriate.
• Measurable impact: Demonstrate how the solution could save time, reduce costs, improve quality, increase productivity, improve decision-making, or create another meaningful outcome.
• User-focused experience: Design the solution around the needs of the people who will actually use it.

A functional prototype or agentic application built on Gemini Enterprise that addresses a well-defined organizational pain point, accompanied by a clear account of the target user persona, legacy workflows replaced, and demonstrated business value.