Find the answers you need with an AI-powered cloud search service. Take advantage of Azure AI speech, vision, and language services to transform raw, unstructured information into searchable content.
Companies hold huge amounts of data, and yet large parts of it are not stored in a structured way or easily searchable. Everyone wants to find relevant information about a given topic without the need to manually go through documents, images and videos – even if they are stored digitally. Take advantage of Azure AI speech, vision, and language services to transform raw, unstructured information into searchable content. During the Knowledge Mining Proof of Concept, we will show you how to do it.
The PoC includes: envisioning and detailed gathering of requirements, solution design customized to your organization's needs, the configuration of storage and services, implementation of a document recognition mechanism, custom skills creation (up to 3 skills), index creation, search engine implementation, Web API configuration, Web application, and front-end design, testing and implementing corrections, deployment and system manuals.
The PoC stages:
1. Envision: gathering specific requirements, setting the criteria of success for implementation, documents structure review and format definition,
2. Plan: project delivery plan, solution design,
3. Build: Azure services configuration, search engine implementation, Web API configuration, Front-end design and implementation,
4. Test: acceptance process, essential test cases specification, corrections implementation,
5. Deploy: solution deployment, establishing the roadmap for further development.
Factors which might affect the estimated pricing: number of documents, number of data sources, front-end design and Web App functionalities, travel and requirement for on-site work, the complexity of document upload process. The plan is approximate, based on earlier implementations – a detailed timeline will be confirmed after the final scoping session.