January Newsletter
Happy New Year!
I’m excited to share an update on my startup, Data Discourse AI. I've started a monthly newsletter, where I’ll be sharing updates and insights from our startup journey.
I’d love for you to come along for the ride. And if you ever have feedback, ideas, or advice, I’d truly welcome it.
So lets get going! This month, we have two main topics and a quick survey.
DDAI Update
The enterprise data stack defined
A quick survey (only 4 questions.)
Warm regards,
Craig and the DDAI team
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🚀 DDAI Update:
Official Launch & What’s Ahead
After months of building, refining, and stress-testing, we’re officially launching DDAI. Q4 was all about getting the foundation right — and here’s what we achieved:
1. Product Upgrade: From MVP to Scalable v1.0
We completed the transition from a scrappy MVP to a robust, flexible v1.0 release. Our codebase is now more modular, enabling fast iteration, new features, and smoother onboarding. The app is ready to scale.
2. New Pricing Model
We developed pricing that aligns with our core customer segments. Plans now start at just $89/month — giving growth-stage SaaS and tech companies access to powerful AI analytics without enterprise bloat.
3. Pre-Seed Momentum
We secured our first outside capital: a $50K angel check as part of our $500K pre-seed round. We’re actively raising to fill the round this quarter, aiming to extend runway and accelerate customer acquisition.
4. We’ve Locked in Our ICP—and We’re Going to Market
We’ve zeroed in on RevOps leaders at SaaS and tech companies—
operators tasked with aligning sales, marketing, finance, and leadership, yet stuck with fragmented data, brittle reporting, and endless custom requests.
And we’re launching a full GTM motion to reach these teams:
LinkedIn, newsletter, and email outreach
Co-marketing through our partner marketplaces (HubSpot, QBO, Stripe and Snowflake)
Performance marketing channels like Capterra and GetApp
A scalable affiliate marketing engine targeting Youtube influencers, HubSpot agencies and fractional CFOs. Check it out HERE
The Journey Begins
The DDAI engine is running — and 2026 starts now with the goal of landing our first 100 paying customers with speed and focus. If you’re excited about where we’re headed, share DDAI with a founder, join our affiliate program, or just reply with feedback. Every bit helps.
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⚙️ The Enterprise Data Stack Defined.
Enterprises know that decisions are only as good as the data behind them. That’s why they invest millions building a modern data stack: an integrated system that pulls data from across the business, cleans and structures it, and makes it usable for reporting, forecasting, and AI. It’s not easy—but it’s worth it.
What is the enterprise data stack? It’s made up of:
Data ingestion from dozens of siloed tools—CRMs, accounting, support and advertising systems—via ETL pipelines like Fivetran, Airbyte, or custom APIs.
Warehousing and governance in platforms like Snowflake, Databricks, or Google BigQuery, where all business data is centralized, secured, and made accessible for downstream analytics.
Data transformation and modeling using tools like dbt or custom SQL pipelines to define business logic—things like ARR, CAC, churn, MRR, revenue by segment, and more.
Semantic layers to standardize how metrics are calculated across teams, ensuring everyone is operating from a shared source of truth.
Dashboards and AI tools such as Power BI, Looker, Tableau, Sigma, or Mode that make insights consumable across finance, growth, marketing, Rev Ops and customer success teams.
Enterprises build this because it pays off: faster decisions, fewer reporting errors, tighter planning cycles, and the ability to tie revenue outcomes to specific actions.
But for many companies, building this stack is out of reach. It takes a team of engineers, a long setup runway, and constant maintenance.
That’s where DDAI comes in.
We deliver the enterprise data stack—out of the box. By building on Snowflake’s enterprise-grade platform and layering in pre-integrated models, metrics, and a conversational AI interface, DDAI gives SaaS and tech leaders access to the same insights large companies rely on—without the complexity.
No engineers required.
No dashboards to build.
No data silos or stale reports.
We connect to your core systems (HubSpot, QuickBooks, Stripe), map them to our harmonized common data model, and let you ask business questions in plain English—getting back clear, trusted answers in seconds.
What takes an enterprise 6–12 months to build, you get in a day—with the power and trust of Snowflake under the hood.
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📝 Please Take our Quick Survey
This survey is only 4 questions and should only take you 2 minutes.
1. On a monthly basis, what would a tool like DDAI reasonably be worth to your team?
2. At what point would the price start to feel too expensive for the value provided?
3. What would need to be true for this to feel like a “no-brainer” purchase for your team?
4. What’s the main reason you’d consider using a tool like this?
