๐๐จ๐ฐ ๐ฉ๐๐ซ๐ญ ๐จ๐ @PetaSight!
Your Proactive Insight Engine | Structured Data Analysis for Business Leaders | Instant AI Data Analyst Team
Weโre excited to announce that @PetaSight has acquired Babbage Insight!
https://t.co/euJPIaJyAH
This strengthens more than insight generation in life sciences primary market research. It strengthens ๐ ๐จ๐ฏ๐๐ซ๐ง๐๐ง๐๐, ๐ฏ๐๐ฅ๐ข๐๐๐ญ๐ข๐จ๐ง, ๐๐ง๐ ๐ญ๐ก๐ ๐๐ฎ๐๐ข๐ญ๐๐๐ข๐ฅ๐ข๐ญ๐ฒ organizations increasingly need.
#LifeSciences #AI #Governance
As a business leader, you need powerful insights to set the overall direction for the quarter or the year. But what comes next is typically harder - strategically moving in that direction.
That requires a very different kind of insight - not the big-bang kind, but small, high-frequency ones. We call them fuel insights.
Hard? Not anymore.
An AI-powered Proactive Insight Engine like Babbage is built precisely for that - to help your business move toward its goals at a pace you never thought possible.
@karthiks@manubhardwaj
The second episode of Data Chatter Season 2 is out now!
Subscribe to Data Chatter (podcast link in comments) to stay updated on how business leaders are adapting to the dynamic world of data-driven decision-making ๏ฟฝ๏ฟฝ๏ฟฝ a world thatโs being rapidly reshaped by AI and Proactive Insight Engines like Babbage.
@karthiks
In our latest Substack post (link in comment), we explore how the world is slowly warming up to the idea of proactive insights.
A Proactive Insight Engine drives continuous improvement across business processes and workflows - helping organizations compound their gains over time.
While most companies still operate in a reactive mode (using dashboards and reports to explain what already happened), itโs clear that the future of data-driven decision-making is proactive. Thatโs where the next wave of competitive advantage truly lies.
AI is changing how business leaders leverage data analytics (reactive -> proactive insights). And that calls for revival of our CEO's podcast - Data Chatter (search for it in your fav podcast app and subscribe).
The first episode of season 2 will drop the coming week. By the way, today happens to be the International Podcast Day, so great timing for us to be making this announcement.
While season 1 of Data Chatter had been about how data scientists, academics, and technologists build models and code, in the new season, we are dong things differently. This time, @karthiks will be speaking with the data users instead of the the data practitioners.
And that means, in the episodes to come, you will get to hear from CEOs, founders, and business leaders on how they are making data-driven decisions today, the challenges they face and how they think AI is going to change it all (or not).
Alright, so do subscribe to 'Data Chatter' on your favourite podcast handle. You can also subscribe to https://t.co/6WlXsVanev to get notified every time a new episode drops!
Together, let's gear up for a world of Proactive Insights!
On the occasion of International Podcast Day, I'm happy to announce that my podcast Data Chatter is (finally) making a come back!
Season 2 starts dropping next week. This time, I'll be talking to business leaders to understand their relationship with data!
2/
From pair programming to piloting: building independent AI data analysts
by @karthiks, co-founder @BabbageInsight
๐ก LLMs can write code, but they also hallucinate.
๐ก Humans plan. LLMs โฆ improvise.
๐ก Pair stats + LLMs = real insights.
In our latest blog, we highlight an interesting 2X2 matrix for looking at how organizations are approaching AI adoption, especially for the Business Intelligence use-case.
We make the case that the Proactive Insight Engine approach, is a clear winner.
Check out the blog here: https://t.co/wBky3Av785
Here's the swipe-able carousel: https://t.co/JtJ3FslJYw
A recent study revealed that 71% organizations (that were surveyed), were 'piloting' AI, but only a meager 5% had successfully scaled AI. This needs to change.
In our latest whitepaper, we make the case that auditability is the missing link between AI adoption at scale and the pilots.
Do check out the full paper at: https://t.co/pUI8DRhOCD
At Babbage - your Proactive Insight Engine - auditability will always be a core aspect of the product. Because as a business leader, you don't just need insights proactively, you also need to be able to trust it and defend it!
@karthiks
I wanted to thank everyone @BabbageInsight for the support, @karthiks for the chance, @manubhardwaj for the daily drive. And @claudeai for timely interventions and explanations.
@BabbageInsight is hiring! Please join them and turn my code into unicorn material.
We are hiring! Full stack engineers, this time.
Reach out to us at [email protected] with your CV/resumรฉ.
You ๐ฆ๐ฎ๐ฌ๐ญ include a link to your GitHub profile, please... but do not include any cover letter content ๐ .
#hiring#remote#fullstack#programmer#india#llm#ai
Everybody is tired of AI hallucination. At Babbage Insight, we got so tired of it so early, that we decided to pioneer the tagline "we are not a copilot!"
Spoiler alert: it turned out not to be a good idea. Business leaders do want to ask questions after all. But ๐ฐ๐ก๐๐ญ are the sorts of questions they want to ask?
Show me the evidence. Dig deeper.
And that's why at Babbage, we have pioneered the Auditable AI Insight, where anything we show you is evidence-based, queryable and instantly proved.
Read it here! https://t.co/ivk3dJXR7L
Today, Babbage needs to know the key metrics of a business for it to deliver on its Proactive Insight Engine promise.
But it's definitely possible that at some point Babbage will be able to suggest these metrics / KPIs on its own. All that it would need to know then is the 'business philosophy' of a company. Hard, but possible.
This is what we talk about in our latest blog. https://t.co/DVSAzTA1k9
At Babbage, we have been asking ourselves this: how would AI change the way we approach setting up and measuring KPIs?
KPIs, OKRs, KRAs etc. are useful for alignment. But at the end of the day, these are all mere proxies for actual goals. They are susceptible to gaming. Also, they remain fairly static, even when business conditions are dynamic. In fact, 60% of managers already believe their KPIs need improvement. So could AI do something here?
The problem is, AI will always struggle to define relevant KPIs unless it can first learn the intrinsic business philosophy of any organization. The semantic layers that exist today however, do not encode the deeper strategic narrative or explain why a metric matters or how its relevance shifts with context. But a Proactive Insight Engine like Babbage changes that.
In our latest blog - https://t.co/FEI5gZzQgi - we talk about the emergence of KPAI (KPIs enabled by AI) where firms get to use AI to define smarter, more aligned proxies and see "measurable improvements" as a result.
The human role could soon evolve from policing stale dashboards to focusing on clarifying core business objectives and ensuring that these AI-driven, adaptive KPIs truly guide the organisation towards its strategic 'true north'.
Whatโs your take on this?
Bab is interning with us at @BabbageInsight
His job is to occasionally talk about things that we are thinking about / building at Babbage. Like how he explains here, the disruption likely to happen in seat-based pricing for SaaS companies.
PS: Post his internship, shall we give a full-time offer to Bab? Like is he good? What do you think?
#proactiveinsight #babbage