AI Data Center Solutions
AI Data Center Solutions
1
Identify legacy systems with possible valuable data. The data can online or offline or archived.
2
Upgrade the legacy systems to a more recent contemporary, possibly supported, same technology platforms.
3
Secure the data using modern cryptography and security guidelines as the data would have been dormant for many years and may be vulnerable.
4
Access the data with native applications and classify the data using criteria’s of usefulness.
5
Consolidate and update the systems to get onto a supported version with appropriate API access. Where possible we can migrate flat data to more appropriate systems to reduce costs and support of legacy systems.
6
Access valuable IP data via more modern interfaces that preserve workflow and programmatical manipulation and create modern interfaces for use. Create custom views of the data for the customer to identify key data.
7
Integrate search and dashboards
Use advance tools such as Kibana and Elastic search to create BI systems to further identify useful information.
8
Use AI Embedding and Vector’s to apply metadata for indexing purposes in advance databases such as Qdrant for use in advance systems.
9
Create and deploy advance, modern systems such as AI chatbots, unified social reporting dashboards, advance search systems and custom modern applications.
10
Turnkey micro applications to further enhance the surfaced data for the AI chatbots and dashboards. Think about stock tickers continuously displaying new information as it is identified in your dataset.