In-Place Search

A New Search Paradigm

Composable In-place Search

“In-place search -> Collect -> Store” Edge, data in motion, in an observability datalake, Timeseries and Log Stores

Faster time to insights and actions

The right data is discovered, searched, visualized, and then either presented as Composable decision boards or alert notifications.

Reduce complexity and cost

Associated with collecting, moving, indexing, storing, and then searching the data, increasing the TCO.

Remove data silos

Low Code / No Code bots invoke a universal query language that can “In-place search” at the edge, across an observability data lake, any time-series database, or custom search tools like Splunk, Elastic

Ease of use

Low Code / No Code bots make it easy for any Citizen developer to use search.

Search Bots

RDA Bots Automate Data Ingestion, Data Processing and Data Routing

Source Bots
Source Bots Retrieve data from a Data. Source either in Streaming or Batch Mode
  • Filter Data
  • Select Subset of Columns
  • Compute New Columns
  • Fix Input Data
  • Aggregate Input Data
Sink Bots
Sink Bots Send data to data destination such as Data lake or other Endpoints
  • Enrich Input Data Using a Dictionary
  • Convert Input Data Types
  • Validate Input Data Model
  • Random Sampling of Data
Transform Bots
Update Bots transform or update the input data and produce new data
  • Perform NLP Sentiment Analysis
  • Perform Unsupervised Clustering
  • Classify Input Data
  • Predict Time Series Data
  • Classify using GPT-3