AI Agents for B2B Reporting

Connect your data and build AI agents that safely answer your users' questions — with text, charts, and tables.

Y Combinator logo Backed by Y Combinator
MCP

MCP Server

Reporting Agent

Database
Database
MariaDB PostgreSQL MySQL
Chat
Ready to dive in?

How it works

Step 1

Connect your database

All Inconvo needs is a database connection. Your agents understand most of your data out-of-the-box — you can add context later through the semantic layer.

Table/column toggle
Computed columns
Column units
Table prompts
Tenant scoping
Join control
Computed Column
Column toggle
card_number
Column unit
id quantity subtotal tax discount card_number total
1 5 100 10 5 ****1234 105
2 3 75 7.5 0 ****5678 82.5
3 8 200 20 10 ****9012 210
Step 2

Integrate your agent

You can integrate your Inconvo agents via our API/SDKs or deploy them as MCP servers on your domain with built-in OAuth support in just a few clicks.

NodeJS SDK
MCP OAuth
Response Streaming
Custom MCP Domain
MCP Server
Tools
get_data_summary
start_data_analyst_conversation
get_active_conversation_id
message_data_analyst
MCP

MCP Server

https://mcp.yourdomain.com/mcp
Step 3

Launch

Make your reporting agent available to your users wherever they are — in your app, or other tools like ChatGPT, Claude or Microsoft Copilot.

Agent traces
ChatGPT Apps SDK
Conversation logs
Usage analytics
MCP

MCP Server

https://mcp.yourdomain.com/mcp

Reporting Agent

Inconvo handles the details

Multi-tennancy

Observability

Inconvo shows every decision a data agent makes, making it easy to debug and improve.

Input
Agent Step (1/2)
getSchemasForTables
Agent Step (2/2)
databaseRetriever
select_table_name
set_context_filters
define_operation_params
set_msg_derived_filters
build_query
execute_query
decide_complete
Response

Conversation State

We'll manage the data agent conversation state to support contextual multi-turn interactions and follow-ups.

How many units did we sell this week?

You sold 300 units.

And that same week last year?

Last year was 200, so 50% more this year.

Usage analytics

Messages

2.4k

↑ 20%

Schema Introspection

Safe Queries

We validate queries before converting to SQL ensuring they are always safe to run.

1 {
2   "tableName": "orders",
3   "operation": "aggregate",
4   "operationParams": {
5     "sum": ["quantity"]
6   },
7   "tableConditions": [
8     {
9       "column": "orga",
10       "operator": "equals",
11       "value": 1
12     }
13   ],
14   "messageConditions": {
15     "AND": [
16       {"created_at": {"gte": "2025-10-01"}},
17       {"created_at": {"lte": "2025-10-31"}}
18     ]
19   }
20 }
organisation_id
equals
1

READY TO START BUILDING?

Create your AI Reporting Agent for free

Inconvo will take you step-by-step through the process of creating your first AI Reporting Agent in just a few minutes.

Simple pricing that scales with you

Free

Get started with a testing your AI Reporting Agent before deploying to your customers for free.

Always

$0/mo


Includes

  • 1 AI Reporting Agent
  • 10 tenants
  • 100 messages

FEATURES

  • Provisioned domain
  • Database connection
  • Basic conversation logs
  • Ticket support
Most Popular

Pro

Production-ready AI Reporting Agents with extended features for scaling companies

STARTING AT

$99/mo


MCP server with

  • 3+ AI Reporting Agents ($25 per agent/mo thereafter)
  • 300+ tenants ($1 per tenant/mo thereafter)
  • 1000+ messages ($0.10 per message thereafter)

FEATURES

  • Custom domain
  • Increased scale
  • Higher usage limits
  • Slack support

Enterprise

Get started with AI Reporting Agents for free, with the future to grow

TO LEARN MORE

Contact us


MCP server with

  • Custom AI Reporting Agents
  • Custom tenants
  • Custom messages

FEATURES

  • SAML
  • Priority support
  • SLAs
  • Success manager (CSM)

FAQ

Who is Inconvo for?

If you would like your users to be able to use your data in AI applications like ChatGPT then Inconvo is for you. If you either have no user-facing data, exclusively simple static dashboards, or you want your own staff to chat with internal company data then Inconvo is not the right fit.

What's the primary use case for Inconvo?

Inconvo lets your users ask questions about their data within AI applications like ChatGPT. It ensures data queries run safely, with security, access control, and observability handled automatically.

What databases does Inconvo support?

Inconvo will only support SQL databases at least in the short to medium term. We support PostgreSQL, MySQL, MsSQL and Redshift today. If you have a database you would like supported please get in touch.

Can Inconvo handle multi-tenant databases?

Yes Inconvo is built for multi-tenant databases. The semantic layer lets you define data access scopes at a per-tenant level.

Does Inconvo replace traditional BI dashboards?

No — Inconvo doesn't replace traditional BI dashboards; it complements them by making data accessible in AI apps which operate through natural language. It's particularly good at facilitating ad-hoc questions quickly, without needing to build new reports or dashboards.

How accurate is Inconvo?

Inconvo's accuracy is very high, assuming your data structures and semantics are of good quality. That's of course easy to say but hard to prove. The best way to understand how it performs is to try it on your own data. Note that one of Inconvo's strengths is the ability to help you identify gaps in your data, allowing you to continuously improve your data quality and, consequently, the accuracy of Inconvo. We provide analytics and insights to help you understand where your data can be enhanced for better accuracy

What support is available?

We'll do our best to help you with any issue you encounter with Inconvo. You can get in touch with us via email and chat. On paid plans you get concierge onboarding. This is a video/phoneonboarding session where we take you through the product and make sure you're happy with set up. You also get priority support with your issues answered first.

Does Inconvo copy and store my data?

No — Inconvo does not store your data. Queries run directly against your database, and only metadata like query traces or usage analytics are optionally logged for observability.