Hi HN, we are Liam and Eoghan of Inconvo (https://inconvo.com), a platform that makes it easy to build and deploy AI analytics agents into your SaaS products, so your customers can quickly interact with their data.

There’s a demo video at https://www.youtube.com/watch?v=4wlZL3XGWTQ and a live demo at https://demo.inconvo.ai/ (no signup required). Docs are at https://inconvo.com/docs.

SaaS products typically offer dashboards and reports, which work for high-level metrics but are clunky for drill-downs and slow for ad-hoc questions. Modern users, shaped by tools like ChatGPT, now expect a similar degree of speed and flexibility when getting insights from their data. To meet these expectations, you need an AI analytics agent, but these are painful to develop and manage.

Inconvo is a platform built from the ground up for developers building AI agents for customer-facing analytics. We make it simple to expose data to Inconvo by connecting to SQL databases. We offer a semantic model to create a layer that governs data access and defines business logic, conversation logs to track user interactions, and a developer-friendly API for easy integration. For observability we show a trace for each agent response to make agent behaviour easily debuggable.

We didn’t start out building Inconvo, initially we built a developer productivity SaaS from which we pivoted. Our favourite feature of that product was its analytics agent, and we knew that building one was a big enough problem to solve on its own so we decided to build a developer tool to do so.

Our API is designed for multi-tenant databases, allowing you to pass session information as context. This instructs the agent to only analyse data relevant to the specific tenant making the request.

Most of our competitors are BI tools primarily designed for internal analytics with limited embedding options through iFrame or unintuitive APIs.

If you’re concerned about AI SQL generation, we are too. In our opinion, AI agents for customer-facing analytics shouldn’t generate and run raw SQL without validation. Instead, our agents generate structured query objects that are programmatically validated to guarantee they request only the data allowed within the context of the request. Then we send validated objects to our QueryEngine which converts the object to SQL. With this approach we ensure a bounded set of possible SQL that can be generated, which stops the agent from hallucinating and running rouge queries.

Our pricing is upfront and available on our website. You can try the platform for free without a credit card.

If you want to try out the full product, you can sign up for free at https://auth.inconvo.ai/en/signup. As mentioned, our sandbox demo is at https://demo.inconvo.ai/, and there’s a video at https://youtu.be/4wlZL3XGWTQ.

We're really interested in any feedback you have so please share your thoughts and ideas in the comments, as we aim to make this tool as developer-friendly as possible. Thanks!

Looks nice. I didn't see any time series use for trend analysis, will you be adding support for that? I think that's the area where I've seen the most demand for this type of assisted data exploration.

I also noticed that you have your org id in your LLM trace - does that mean that you are trusting your agent to limit the orgs it queries? If so that seems quite dangerous as it could be tainted by prompt injection, no?

I'm intrigued by this as it's a problem we're facing. However, I don't really understand pricing in the context of targeting multi-tenant SaaS companies.

> 3+ agents ($25 per agent/mo thereafter)

What is an agent? Specifically, how are these counted?

> 25+ active tables ($5 per table/mo thereafter)

This is clear and concise, but just doesn't resonate with me as a good lever for pricing. I'm just going to our our data team run a transformation to consolidate tables.

Number of rows/colummns ingested feels a lot more natural to me

> 15+ seats ($10 per user/mo thereafter)

How is a seat defined in the context of multi-tenant Saas?

Let's say company A has 200 employees in our system, but only 5 of them interact with the agent monthly. Are we billed:

* 1 seat - company A

* 200 seats - each employee of Company A

* 5 seats - only the users that interacted with the agent.

Great launch—this is a neat solution for embedding AI-powered analytics into multi-tenant SaaS products!

A couple of thoughts/questions that came to mind:

Time series and trend analysis: You mentioned support for queries like “Show me the sales trend over the last quarter.” Have you considered enabling more complex trend detection, such as anomaly spotting (e.g. “flag any week where sales dropped >15% vs previous week”) or seasonality adjustments (comparing YoY trends)? I think these kinds of features could greatly enhance the exploratory experience for non-technical users.

Control and validation of generated queries: The semantic-layer + WHERE clause strategy sounds very robust—it’s reassuring to see this deterministic guard against prompt injections or tenant leaks. Out of curiosity, do you provide tooling to audit or review agent-generated query objects before they run, especially for initially onboarding new clients? That kind of transparency could boost confidence in more security-conscious customers.

Overall, love the direction—AI-powered analytics agents have a ton of potential. Looking forward to seeing how this evolves!

Is it purely chat based (ad-hoc) or users can make dashboard like “cards” for common queries they have? (Imagine the stripe dashboard MRR, today’s revenue, failed charges, etc)

Congratulations on the launch, looks great. Do you also support Google Sheets? We are building our dashboards in Sheets right now and that’s a big pain. Looking for alternatives.

Congrats on your launch! I see you are using Recharts in your demo to show some nice charts after / withing the chat responses which is very nice.

Does the backend only create the chart data and the chart itself is rendered in the frontend? Or put differently: Can you use any chart library to render this data? Do you support multiple chart types?

Congrats on the launch, any plans to support ClickHouse?

ps. I work for ClickHouse and happy to help

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