100x More Efficient.
100% in Your Cloud.
Welcome to the age of Serverless AI. The latest features with this release improves the efficiency gains by 100x. This further drives acceleration and strengthen guardrails for generative AI responses, paving the way for business user led innovation in the enterprise.
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Fine Tuning-1

End-to-end Fine Tuning

As we worked on our Small Model capabilities, we quickly realized that there was a night and day difference between the generic versions of such models vs. even models fine tuned on hundreds or thousands of examples for a cost of about $100. But doing model fine tuning requires significant data science expertise today.

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Collecting user feedback on enterprise data is also a chore because the model needs the context data such as what vectorDB snippets were passed to the Language Model as part of the chat interaction that the user provided feedback on. So, Aible automated the process end-to-end, from collecting data from end-users, setting the correct fine tuning parameters, automatically doing the fine tuning, to making the fine tuned model available as a serverless option in Aible. Essentially, users just have to provide feedback using thumbs up/down or editing chat responses - then once enough data has been collected, simply click a button to fine-tune.No expertise required. Of course, expert users can set the fine tuning parameters if they want. This feature is currently only available on GCP & AWS for a subset of models such as Mistral and Llama. We expect to add more clouds and models soon.

End-to-end Fine Tuning

Fine Tuning-1

As we worked on our Small Model capabilities, we quickly realized that there was a night and day difference between the generic versions of such models vs. even models fine tuned on hundreds or thousands of examples for a cost of about $100. But doing model fine tuning requires significant data science expertise today.

Read More
Collecting user feedback on enterprise data is also a chore because the model needs the context data such as what vectorDB snippets were passed to the Language Model as part of the chat interaction that the user provided feedback on. So, Aible automated the process end-to-end, from collecting data from end-users, setting the correct fine tuning parameters, automatically doing the fine tuning, to making the fine tuned model available as a serverless option in Aible. Essentially, users just have to provide feedback using thumbs up/down or editing chat responses - then once enough data has been collected, simply click a button to fine-tune.No expertise required. Of course, expert users can set the fine tuning parameters if they want. This feature is currently only available on GCP & AWS for a subset of models such as Mistral and Llama. We expect to add more clouds and models soon.
KPI-2

Why Behind the KPI

Today most companies have complex pivot tables that show them how business KPI have changed week over week, month over month, etc. Then when execs ask about specific shifts analysts have to scramble into action to explain exactly why that shift happened. Aible unlocks the data trapped in your Spreadsheets with our KPI pivot table analysis to quickly find trends and unexpected shifts in your KPIs.

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The Aible pivot table analysis will also show what underlying groups are contributing to these shifts, removing the need to wait on additional information before you take action on important behavior changes. The key insights are presented via end-user-customizable generative Ai summaries.

Why Behind the KPI

KPI-2

Today most companies have complex pivot tables that show them how business KPI have changed week over week, month over month, etc. Then when execs ask about specific shifts analysts have to scramble into action to explain exactly why that shift happened. Aible unlocks the data trapped in your Spreadsheets with our KPI pivot table analysis to quickly find trends and unexpected shifts in your KPIs.

Read More
The Aible pivot table analysis will also show what underlying groups are contributing to these shifts, removing the need to wait on additional information before you take action on important behavior changes. The key insights are presented via end-user-customizable generative Ai summaries.
Frame 5116

A/Z Testing for Rapid Experimentation

Experimentation is key to any data science project. But this becomes complicated for generative AI applications, because different users may find different responses more attractive. Aible already makes it possible for end-users to make the GenAI app their own by changing tones, few-shot learning, etc.

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Now, organizations can try out many different combinations of settings, from the selected Language Model, model settings, tone, prompt augmentation, few shot learning, or VectorDB settings to identify the best combinations that maximize end-user satisfaction. They can continuously deploy, compare and monitor improvements to chat apps with such Aible A/Z testing.

A/Z Testing for Rapid Experimentation

Frame 5116

Experimentation is key to any data science project. But this becomes complicated for generative AI applications, because different users may find different responses more attractive. Aible already makes it possible for end-users to make the GenAI app their own by changing tones, few-shot learning, etc.

Read More
Now, organizations can try out many different combinations of settings, from the selected Language Model, model settings, tone, prompt augmentation, few shot learning, or VectorDB settings to identify the best combinations that maximize end-user satisfaction. They can continuously deploy, compare and monitor improvements to chat apps with such Aible A/Z testing.
aible-agent

Aible Agent for Solving Complex Business Problems (Beta)

Customers want to use AI to solve end-to-end problems like reducing friction or risk in processes like Order-to-Cash or Procure-to-Pay. In our Valentine’s Day release we launched the new Aible Anywhere offering that enabled organizations to transform their end-to-end processes by leveraging combinations of classical AI (predictions, optimizations, recommendations) and generative AI (information extraction, summarization, communication). But our customers asked, “Can’t an AI also create the Aible Anywhere flow for me?” Aible Agent Builder (Beta) does exactly that, summarizing insights and recommending actions across multiple datasets and Aible projects using Aible agents.

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Our simple flow allows you to describe the tasks you would like the agent to perform and then the Aible Agent Builder will propose an action plan for user feedback, then build the necessary steps to accomplish the tasks and automatically link relevant projects containing the necessary data.

Aible Agent for Solving Complex Business Problems (Beta)

aible-agent

Customers want to use AI to solve end-to-end problems like reducing friction or risk in processes like Order-to-Cash or Procure-to-Pay. In our Valentine’s Day release we launched the new Aible Anywhere offering that enabled organizations to transform their end-to-end processes by leveraging combinations of classical AI (predictions, optimizations, recommendations) and generative AI (information extraction, summarization, communication). But our customers asked, “Can’t an AI also create the Aible Anywhere flow for me?” Aible Agent Builder (Beta) does exactly that, summarizing insights and recommending actions across multiple datasets and Aible projects using Aible agents.

Read More
Our simple flow allows you to describe the tasks you would like the agent to perform and then the Aible Agent Builder will propose an action plan for user feedback, then build the necessary steps to accomplish the tasks and automatically link relevant projects containing the necessary data.
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