Enhance Customer Support with AI-Powered Conversations

Elevate your customer support experience with Agent Cloud, where conversational AI bridges the gap between complex queries and instant resolutions, ensuring customer satisfaction and loyalty.
1

Provide knowledge retrieval for your customer support agents

Provide immediate, accurate responses to customer inquiries, reducing wait times and enhancing the support experience.
24/7 Support Availability: Offer round-the-clock customer service with agents capable of handling a wide range of queries, ensuring no customer is left waiting.
Scalable Support Solutions: Easily scale your support capabilities to handle peak volumes without compromising on response quality or speed.
2

Quickly triage customer feedback

Utilize conversational AI to understand feedback on aggregate and respond to individual customer needs and preferences, creating a more personalized and engaging support experience.
Tailored Support Responses: Leverage AI to analyze customer history and context, providing personalized support and recommendations.
Enhanced Customer Understanding: Gain deeper insights into customer behavior and needs through AI-powered analysis, driving continuous improvement in service strategies.
3

Augment support teams data connected AI assistants

Stand up agent groups that can augment your support teams and triage through more complex use cases than simple chatbots can offer.
Issue Prevention: Use AI to identify and address potential issues before they escalate, reducing customer frustration and support tickets.
AI Augmented teams: Leverage agent teams that can support your team for more complex use cases.

Overview of all the features

The end to end RAGĀ pipeline

Select your connector

Use our collection of data sources to sync data from other systems like confluence or upload your own pdf, docx, txt or csv file.
When selecting systems like databases (postgres, snowflake, bigquery) you can select tables and even columns to ingest.

Prep your data

For files you can provide instructions on how to split and chunk your data. Leverage Open AI latest text-embedding-3-smallĀ for embedding or select from open source models like BGE/base.

Vector store your data

Once data has been embedded the platform will store your data within a vector database. We also expose

Keep data fresh

Select what frequency you would like to sync data from the source. This can be manual, scheduled or a cron expression. This means users can query fresh data and know how recent the source was updated.

Start chatting with your data!

Now that data is synced, simply create an agent with your choice of LLM and start a session to talk to your data.

Privately chat to your data in your cloud.

Get started with Agent Cloud Community edition today or talk to us for enterprise enquiries.