Enterprise AI is moving fast. The organizations winning aren't the ones experimenting, they're the ones deploying.
https://t.co/V33T3qcGHe CTO and Co-Founder Ram Venkatesh joins A Global Tech Podcast to discuss why governance and business context separate impressive AI from reliable AI, and how organizations are putting agentic AI to work in real operational workflows.
🎙️https://t.co/eQAp30HsCG
Next Tuesday: See how Koch Ag & Energy Solutions, LLC reduced invoice reconciliation from hours to minutes with AI agents.
Plus, hear how enterprise AI agents are expanding into additional business workflows.
Save your spot: https://t.co/FTfc2KRErq
AI agents should adapt to how business users already work, not force them to translate their expertise into code.
Our Co-founder and CTO, Ram Venkatesh, joined @bgracely on @TheEntAIShow to unpack how https://t.co/V33T3qcGHe enables business users to build agents based on their own understanding of a process – no IT required.
🎧Listen here: https://t.co/YN8pMV0vLF
AI agents shouldn’t just access your data. They should understand it.
With AI-powered semantic understanding, teams can ask questions in plain English and get answers grounded in real business context.
This is how enterprise AI moves from queries to real understanding. Learn more: https://t.co/MVJ6EGktr8
Security for AI agents comes down to one question: where are they running? If the answer is outside your environment, you don't have full control.
@paulcodding, Co-Founder and SVP of Product and Customer Experience, shares what it actually takes to secure agents in production – why keeping agents inside your own infrastructure matters, how layered security + role-based access work in practice, and what full visibility actually looks like.
The era of manual data wrangling is over.
AI agents are transforming the Office of the CFO with 90%+ automation across invoice reconciliation, payments, and AP workflows, cutting processing time from days to minutes.
With mathematical precision and hands-off reconciliation, teams gain accuracy, control, and faster outcomes.
The biggest misconception in enterprise AI: the model is the differentiator. It’s not. What actually matters is whether your agents can truly understand and operate on your data.
🎥 @paulcodding , Co-Founder and SVP of Product and Customer Experience, breaks down what separates experiments from real systems.
I’m super excited about a new arts festival we’ve been working on here in Santa Cruz. The Ripple Effect Arts Festival is a celebration of the amazing artistic talent in Santa Cruz county. This is the inaugural year but hopefully it will grow and grow! https://t.co/fautHCy2KC
When AI moves into finance, the stakes shift entirely. It stops assisting and starts deciding, and that changes everything about how you need to govern it.
Finance requires:
•zero error tolerance
•real audit trails
•the ability to step in instantly
Co-Founder and SVP of Product and Customer Experience @paulcodding on governing in finance. ⬇️
Ready to move from AI experiments to production?
Join us March 25 at the Snowflake Silicon Valley AI Hub for a hands-on workshop on building production-ready AI agents in Snowflake.
Learn to build with Python, SQL, and runbooks, connect to enterprise data with zero-copy access, and deploy securely at scale.
Register: https://t.co/ymoc0WG4vK
We’ve loved connecting with everyone this week at the @Gartner_inc Data & Analytics Summit. If you’re in Orlando, stop by Booth #207 and join our session today at 2:00 PM ET:
“From Data Silos to Intelligent Action: Building Enterprise AI Agents That Work with Your Data.”
See live demos and learn how organizations are moving beyond stalled automation to AI agents that execute real work across enterprise data.
Most AI agent deployments stall after pilots. The missing piece? A semantic layer that lets agents understand enterprise data across databases and documents.
In our latest blog, Paul Codding, Co-founder and SVP of Product and Customer Experience at https://t.co/V33T3qdewM, shares a bold take:
“The semantic layer is the most underestimated capability in enterprise AI.”
Read more: https://t.co/7jvbxe7T50
Getting value from enterprise data shouldn’t require SQL or complex pipelines.
Today at the @Gartner_inc Data & Analytics Summit, https://t.co/V33T3qdewM announced the GA of our Semantic Layer, helping AI agents understand enterprise data and enabling business users to analyze structured and unstructured data faster.
Learn more: https://t.co/Kl6oXUFsDo
Bold claim: 2026 belongs to AI agents. We map the ecosystem, the platform play, and a crawl-walk-run path to measurable ROI. Back office to boardroom, this is the autonomy shift. Will your team be ready or left behind? @sema4ai https://t.co/Dz9H6OyQDA
74% of enterprises are investing in agentic AI workflows, and that shift is happening now.
This isn’t about exploration anymore, it’s about execution. Trust is growing, integration is underway, and AI agents are moving into the heart of business strategy.
Learn how to get started: https://t.co/R569N0fXpR
Enterprise AI made simple.
With @sema4ai and Docker’s MCP Gateway, business users can build agents in natural language and connect instantly to tools like Stripe, Box, and Slack.
Secure, scalable, and powerful.
https://t.co/b4YaHMN36O