Three different businesses. One question they all have.
Whether you build software, deliver projects, or run a company. You want to use AI, not become an AI developer!
Not everyone in the world needs to become an AI developer!
You have built software. Your customers want AI in it.
Your customers have used ChatGPT. Now they’re asking why your product doesn’t let them talk to their data. You know you need conversational analytics — the question is whether to build it or embed it.
Building it yourself means venturing into uncharted territory, with big questions about cost and time. And the risk.
- Decisions on whether to use an LLM or build using something else.
- Build a new team who focus on this AI piece only?
- Do I want this feature to be a maintenance burden?
Your entire platform provides value to your customers by processing transactions and providing the necessary reports. Your product is domain-specific, complex and state-of-the-art! Using this, your customers make critical business decisions. These are your strengths.
Let us give you the hype of having an AI Chatbot while providing genuine value to your customers, at a fraction of the cost that customers may incur by pushing Excel data into ChatGPT or Copilot. Transparent and certain cost!
Embedding SmartenBoT takes days, not months — and the capability lives in your product under your brand.
Deploy on-premise, hybrid, or cloud — however your product is deployed.
This multi-tenant-ready product has a complete data cleansing and transformation engine to help you prepare analytics-ready data. You can add computed columns, remove irrelevant data, clean data, transform data, aggregate data, join data from multiple sources, and do much more to have the Agentic AI engine delight your customers.
- Embed inside your UI via REST and JavaScript APIs
- No separate login for your customers — it lives inside your product with SSO
- Inherit your existing security model and user roles — users only see data they're already allowed to see
- Your demos change: prospects ask their own questions
- New users onboard without training — they already know how to ask a question on Google
- Limit the number of dashboards and reports for your customers. Reduce cost and give more results.
- Your product, your pricing – We do not interfere.
- Improve user adoption and ROI. Minimise customer churn.
Five years from now, the ERPs and CRMs that ship without conversational analytics will look like the ones that shipped without mobile apps in 2015. Building this yourself is a real investment. Embedding SmartenBoT is a few days of integration work and a commercial conversation.
You win RFPs. All RFPs ask for Analytics. Dashboards are no longer how you win them.
Your customers have been burned by BI projects before. Six months, a lot of money, and at the end, they got reports that half the users never opened. They’re harder to convince on the next one.
Conversational analytics is a different pitch. Every user immediately knows how to use it. The customer sees value in week one. You stop competing with body-shops and start selling transformation outcomes.
The business model shift
Conversational analytics practices are built on vertical expertise. You’re not competing on who has the cheapest developers — you’re competing on who understands manufacturing, public services, BFSI, or pharma data deeply enough to configure the system correctly. That’s a different firm from the one you’re competing against today.
- Four-week implementation vs six months for traditional BI
- Bring Agentic AI into your tech stack without writing a single line of code.
- Vertical specialisation by you creates a defensible, high-margin practice
- Ongoing tuning and context refinement are a recurring revenue line — not a one-time project
- The consulting work is business-understanding and ETL-writing — it commands consulting prices
- Deploy on-premise, hybrid, or cloud — whichever the project requires
You have the data. You have BI. You’re just not getting enough from it.
Your company has two hundred dashboards from Power BI, Qlik, Tableau, and yes, some of them answer questions on the dashboards! Only thirty dashboards are opened. The rest exist because someone once had a question, and the data team built a report for it. The data team is still buried in one-off requests. Your CEO still asks an EA to pull a number. There is a reporting engine at work, and there is an expert in spreadsheets who is still aggregating data, performing VLOOKUPS and sharing!
SmartenBoT sits atop your transaction systems and lets anyone ask questions. The question gets answered directly — as a chart, as a table, and as plain English. The data team gets to do real work again.
- Q&A on combined data sources like ERP and CRM, not independent bots made by large vendors.
- Sets the ground for ending resources for reporting and dashboarding. What you have made is enough.
- Checking facts, the biggest challenge. A single-line question does not need a dashboard or a report.
Conversational analytics isn’t magic. It needs your data to be in reasonable shape and your business terms defined consistently. We can help with both. But if your data is genuinely chaotic, no AI product will fix that — it’ll just give you confidently wrong answers faster. We’d rather start with an honest assessment than sell you something that won’t land. We usually work with partners but if your system is ready for SmartenBoT, you can get ready with it in a couple of weeks.
How SmartenBoT compares.
Key: Supported · Not supported · Partial or conditional. Pricing shown as relative cost to embed and scale.
| Capability | SmartenBoT Smarten | Power BI Copilot Microsoft | Tableau Next Salesforce | Qlik Answers Qlik | ThoughtSpot ThoughtSpot | Looker Google | Strategy One MicroStrategy |
|---|---|---|---|---|---|---|---|
| Conversational Analytics | |||||||
Conversational analytics as the primary interface Not a feature bolted onto dashboards | |||||||
Works fully when embedded in ISV product Seamless | |||||||
Independent of pre-built dashboards Answers any question, any dimension | |||||||
Multi-turn context retention Follow-up without repeating filters | |||||||
Unlimited conversational queries No per-query or monthly caps | |||||||
| Data Connectivity & Preparation | |||||||
On-premise RDBMS, SAP, flat files Not just cloud warehouses | |||||||
Data cleansing before analysis fill nulls, fix inconsistencies, remove outliers | |||||||
Computed and derived fields Add columns, expressions — without a developer | |||||||
Multi-source data blending ERP + CRM + flat files in one query | |||||||
| Deployment & Security | |||||||
LLM never sees raw data Data queried directly, not passed to AI | |||||||
| ISV Commercial Fit | |||||||
Pricing for ISV embedding Relative cost to embed and scale | Most competitive | High | Very high | Very high | Very high | Extremely high | Very high |
Configured in weeks, not months | |||||||
We may have used Claude and ChatGPT to make this comparison. But we also looked at the other products and this is to the best of our understanding.