Really love this post by @rex_woodbury. Been feeling the same way this year and seeing the same thing play out in our portfolio and pipeline at @Work_Bench.
"New York is perfectly suited to applied AI. Why? Well, because New York is an industry town.
You could make the argument that New York is a (the?) global epicenter for a dozen major industries"
🗽🗽🗽
If you’re an engineering leader, platform architect, or AI team lead inside a regulated financial services enterprise, this one's for you.
What're you building with AI agents in finance -- or what's been slowing you down?
💡 Agentic AI is powerful — but it’s not plug-and-play. MCP helps but it's not the full answer. 🚧
We just published a new post breaking down what it really takes to move multi-agent AI from flashy demos to production systems in finance.
Spoiler:
This is all about the "systems" part of multi-agent systems. We treat vertically-focused agentic AI as a modern engineering frontier with challenging real-world requirements, especially in global regulated environments.
"Context Engineering" is the new buzzphrase💡 but this what we've been doing with our multi-agent workflow automation AI systems⚡️ for enterprise financial services 🏦since Day 1 at @artian_ai#AI#Agents#EnterpriseAI#Finance
There is so much opportunity right now in making AI Agents real for enterprises. The models pack insane capabilities, but to get them into the middle of an enterprise workflow requires significant scaffolding, domain understanding, and context engineering. This is the play.
@ttunguz This is something @prashantreddy has lived through firsthand and has compelling thinking about as he builds @artian_ai, specifically within an enterprise context
You should chat!
@levie Process mapping used to be a dead end exercise which took a tremendous amount of effort but didn't lead to meaningful improvements in enterprise workflows. But, with #AgenticAI workflows, BPM and "automation" (not RPA) can be fully intertwined to deliver true value! @artian_ai
Not all “enterprises” are created equal. Building AI for a 300K-employee, $178B global bank ≠ deploying a chatbot at a SaaS startup.
It’s a different class of challenge:
💰 Risk
🌍 Memory
🔗 Orchestration
🔒 Governance
New post on the @artian_ai blog:
→ https://t.co/EaLaV4mgB6
If you’re building AI for high-stakes, regulated workflows—this one’s for you.
#EnterpriseAI #AgenticAI #AIAgents #Fintech #ArtianAI
99% of the #AI companies out there don't bother to do the hard engineering required to make #Agents work in large enterprises at scale... but are confident that they "have it solved".
Adorable puppy though! 😍
@btaylor Love this, and that's not even the full iceberg! If you were to expand beyond customer service use cases to core business processes in complex enterprises, there's almost as many more. @artian_ai was born from living those pain points!
https://t.co/LywCBl49c4
@levie As @fendien points out, we've lived the pain of these complex enterprise use cases first hand! Global finance is a perfect example to start. That's exactly why we anticipated the current challenges with #Agents and built @artian_ai
https://t.co/LywCBl4H1C