Code & Act On Your Data
  • Introducing Ada

    Autonomous Code Agent For Data

    Build malleable software which typically requires small bits of code, throw it away when it's done.
    Unlock the hidden potential in your data, and automate repetitive tasks.

    Try Now
  • Builder

    Customized Agent Behavior

    Create composable and self-explanatory data units that can be easily consumed by LLM.
    Build custom LLM workflow on top of data units to capture your business logic.

    Start Building
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Automate Repetitive Tasks

Get s&p500 end of day data, and save as csv, the data should contain open, high, low, close, volume, and adjusted close price.

Goal

Unlocking the Full Potential of LLMs with Your Data

Fragmented and Inconsistent Data Sources

Applications often need to integrate data from various sources and extract only the relevant portions. Enterprises are generally resistant to changing how they store data, making it difficult to align these fragmented and inconsistent data systems with LLM requirements.

Garbage in, garbage out

The quality of data to LLM directly impacts the performance of LLMs. Low-quality, unstructured, or poorly labeled data can lead to inaccurate, irrelevant, or even harmful model outputs.

Data Exploration: A Specialized Expertise

Data exploration often becomes a specialized skill held by certain data scientists and programmers. This is because it requires a unique blend of data expertise and coding proficiency. Individuals with this combined skillset are often rare, leading to data exploration becoming the domain of a select few.

Solution

Table Augumented Generation + Autonomous Code Agent

Handle Multiple Data Sources

From your local csv/excel/parquet files to mysql/postgres/sqlserver databases and cloud data warehouses such as Snowflake

https://docs.rebyte.ai

Enrich your data with LLM Friendly Metadata

Auto generate metadata for your data, for example, column names, data types, possible values, column descriptions, value distributions, etc.

https://docs.rebyte.ai

Precisely track how LLM uses your data

Due to unpredictable nature of LLMs, observability is key to understanding how they are using your data, we build agent observability into pipelines, and track how LLMs are using your data

https://rebyte.ai

'Burn After Using' Apps

Write, debug, and run code, allowing user to build apps on the fly, instead of relying on the static, pre-built apps of the past. This opens up a whole new world of possibilities for dynamic, user-centric applications

https://rebyte.ai

How it works

Just 3 steps to get started

    1. Build Metadata Enriched Table

    Integrate and define clean, semantic tables from diverse data sources

    2. Forge Intelligent Agents

    Build intelligent agents by orchestrating LLMs, Tables and other tools

    3. Build User Centric Apps Over Your Data

    Build dynamic, user-centric applications over your data, let agent do the heavy lifting

Use Cases

    Gain insights you never thought possible

    Let AI explore your data and uncover hidden patterns.

    Create beautiful visualizations

    Never need to learn BI tools, let AI do the heavy lifting.

    Statistics Analytics

    You don't need to a data scientist to do predictive analytics.

    Automated Task

    Automate your repetitive tasks and focus on what matters.