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Why AI Automation Projects Stall (And What to Do About It)
AI process automation projects stall for predictable reasons, and most of them aren't technical. After dozens of implementations across regulated industries, here's where teams get stuck and how to avoid it.
Stop Building Dashboards. Build AI Agents Instead.
The chatbot era disappointed everyone. But something different is working: AI agents that pull data from Zendesk, Salesforce, internal databases, and Slack into one conversation. We're deploying this pattern across industries.
We're Building an AI Early Warning System for Viral Outbreaks
CDC reports arrive too late to stop outbreaks. A pharma company asked us to process millions of daily data points from hospitals, labs, and public sources to predict where outbreaks will hit next.
We Built Document AI That Reads Fund Prospectuses at 98% Accuracy
Financial analysts were spending days manually reading 200-page fund documents during filing season. We built a pipeline that extracts performance data, fee structures, and risk factors automatically.
From 48 Hours to 30 Minutes: Rebuilding a Music Distribution Pipeline
A music distributor's upload-to-Spotify pipeline took two days and rejected tracks constantly due to metadata errors. We rebuilt it cloud-native with automated QC. Now it runs in 30 minutes.
Forget the 10x Engineer. Your Whole Team Should Be 2x.
Everyone talks about senior devs shipping faster with AI. The bigger opportunity is the analyst, the project manager, the compliance officer. Most companies won't let their people use the tools that already exist.
Building an SMS Platform That Sends 2 Million Messages a Day
A retail messaging platform needed to handle flash sales, auth codes, and loyalty programs through one API without falling over. Here's the architecture we built and what we learned about messaging at scale.
We Built a Vendor Fraud Detector That Runs Inside Outlook
Companies lose $1.2M per year to invoice fraud on average. KYC protects against customer fraud, but nobody was checking vendors. We built a system that flags suspicious invoices before anyone clicks approve.
From Research Prototype to FDA-Cleared AI: What It Actually Takes
Penn Medicine had an AI model that could contour organs for radiation therapy in minutes instead of hours. Turning that into an FDA-cleared commercial product is a different problem entirely. Here's how we did it.
How We Built an AI System for Distressed Real Estate Investing
A national fund had analysts manually reconciling asset data from dozens of banks, each in a different format. We built an ML pipeline that normalizes it all and scores every deal in real time.
Using Satellite Imagery to Find $1.2B in Sales Opportunities
An energy company's sales team was chasing cold leads. We combined satellite imagery with predictive analytics to score every commercial rooftop in the country and feed high-value prospects straight into Salesforce.
Your Team Has the Data. They Just Can't Get to It Fast Enough.
A VP of IT told us: every time a decision-maker wants a new KPI, it takes weeks for the data team to deliver. We built natural language interfaces that let business leaders query their own systems directly.
Most AI Projects Fail. Here's Why.
CNET's AI articles had math errors. Companies are burning millions on AI that doesn't work. The difference between projects that ship and projects that flop comes down to one question nobody asks early enough.
UNest: How We Helped a Fintech Platform Reach 500,000 Families
UNest makes tax-advantaged investing simple for families. We've been their engineering partner since early days. Plus: our work with the Center on Rural Innovation bringing tech resources to underserved communities.
What We Learned at VivaTech About Medtech, Digital Twins, and Entering the US Market
We went to VivaTech in Paris to meet European startups trying to break into the US. The medtech companies were the most interesting. Here's what stood out and where we see opportunity.
Building Edge AI for NATO's Intelligence Operations
We're working with Siemens and NATO Allied Command Transformation on SeDICA, an Edge AI platform for Joint ISR. From SPARK in Pensacola to SHINE in La Spezia, here's what we're building and why it matters.
How We Support Early-Stage Companies (and Why We Built an Acceleration Network)
A three-stage approach to working with startups: define the goal, build the product, then use our network to fund and scale it. Plus a look at R3 Score, a company rethinking background checks with data.