Inconvo makes it easy for developers to add Ask AI for customer-facing
analytics so that users can ask questions on their data in natural
language.
One API, that delivers answers in text, chart, or table format.
Backed by Y Combinator
Enhance your users' data analysis experience with top-tier conversational AI.
{
"question":
"How many products have I sold per day of the week?",
"conversationId": "conv_c9b1d",
"requestContext": {
"userId": "user_d7adc",
"orgId": "org_99548"
}
}{
"type": "bar_chart",
"message":
"Here's a breakdown of the number of
products sold per day of the week.",
"chartData": {
"data": [
{
"label": "Monday",
"value": 8
},
{
"label": "Tuesday",
"value": 8
},
{
"label": "Wednesday",
"value": 10
},
{
"label": "Thursday",
"value": 12
},
{
"label": "Friday",
"value": 10
},
{
"label": "Saturday",
"value": 10
},
{
"label": "Sunday",
"value": 6
}
],
"title": "Movies Rented Per Day of the Week",
"xLabel": "Day of the Week",
"yLabel": "Number of Movies Rented"
}
}{
"question":
"How many products have
we sold over the past 6 months",
"conversationId": "conv_c9b1d",
"requestContext": {
"userId": "user_d7adc",
"orgId": "org_99548"
}
}You have sold 293 product over the past 6 months.
{
"type": "text",
"message":
"You have sold 293 product over the past 6 months."
}{
"question":
"What were my top 5 selling products last quarter?",
"conversationId": "conv_c9b1d",
"requestContext": {
"userId": "user_d7adc",
"orgId": "org_99548"
}
}| Product Name | #Sold | Revenue | Profit |
|---|---|---|---|
| Mac Mini | 300 | $3000 | $600 |
| Nvidia Digits | 250 | $2500 | $500 |
| Mac Studio | 200 | $2000 | $400 |
| Raspberry Pi 4 | 150 | $1500 | $300 |
| Vector One | 100 | $1000 | $200 |
{
"type": "table",
"message": "Here's a breakdown of the product sales data.",
"tableData": {
"columnNames": [
"Product Name", "#Sold", "Revenue", "Profit"
],
"body": [
{ "Product Name": "Mac Mini", "#Sold": 300, "Revenue": "$3000", "Profit": "$600" },
{ "Product Name": "Nvidia Digits", "#Sold": 250, "Revenue": "$2500", "Profit": "$500" },
{ "Product Name": "Mac Studio", "#Sold": 200, "Revenue": "$2000", "Profit": "$400" },
{ "Product Name": "Raspberry Pi 4", "#Sold": 150, "Revenue": "$1500", "Profit": "$300" },
{ "Product Name": "Vector One", "#Sold": 100, "Revenue": "$1000", "Profit": "$200" }
]
}
}We use your existing data to enable reliable and production-ready Ask AI for customer-facing analytics.
Connect with your existing data sources to retrieve data for Ask AI.
Deploy Ask AI via our API and use it where users have questions on their analytics (e.g. Dashboards, Reports, Chatbots).
Optimize your customer-facing analytics, enhance user experience and drive product decisions with insights.
Use the self-service platform to explore, control and evaluate Ask AI.
Use the API playground to run queries, provide feedback and add examples to your evaluation dataset.
Take full control over the tables and columns that your AI can query.
Curate a dataset of queries based on your users' questions to test accuracy before deployment.
See exactly how well your Ask AI can answer user questions.
We optimize Inconvo for one thing: providing the most accurate answers to your users questions about customer-facing analytics.
Accepts when data to answer the question is unavailable and only answers questions related to retrieval from the connected datasource.
Infers user intent, but always answer factually - outlining any assumptions for easy correction on follow up questions.
Generates data retrieval queries dynamically and remains accurate even as your analytics evolve.