What We Actually Do
Three things. We do them well. We don't do everything — which is, frankly, underrated as a business strategy.
Agent Services
Managed AI agents that handle the work your team is too expensive to do manually and too important to ignore. Email triage, scheduling, research, document analysis, inquiry routing — always on, intelligently routed, with human oversight built in so nothing consequential happens without a human saying so. See how Agent Services works →
AI Consulting
For organizations that need to figure out where AI fits before they start bolting it onto things. We assess your operations, identify what's actually automatable, build you a prioritized roadmap, and stay in the room through implementation. Strategy that ends in production, not a slide deck in a drawer. See how AI Consulting works →
Platform Development
Custom AI platforms built around your specific workflows, integrated with the systems you already depend on — CRM, ERP, email, calendars, APIs — and architected to scale when the pilot becomes the product. We build it. You own it. See how Platform Development works →
Why Lab 317
Look, there are a lot of people selling AI right now. Most of them discovered AI about eighteen months ago and have been very excited ever since. We're not them.
We come at this from operations, not hype. The question we ask first isn't "what AI can we add?" It's "what's breaking, what's slow, and what would your team actually use if it worked?" That's a different question. It leads to different answers. The answers are less exciting in a press release and significantly more useful in practice.
We care about the handoff.
A lot of AI engagements end at deployment. Ours don't. Whether that means training your team, embedded coaching through the first weeks of real-world use, or building oversight workflows that keep humans where they belong — we stay involved until the thing is actually working. Not just technically running. Actually working.
We're honest about what AI can't do.
AI agents are remarkable. They are also not magic. They make mistakes. They need good specs. They need human oversight on decisions that matter. We will tell you this before you hire us, during the engagement, and after — because the clients who know this get dramatically better results than the ones who don't.
We don't train on your data.
Everything we build uses encryption, SSO, and role-based access. Your data is yours. Your clients' data is yours. That's not a feature we lead with in sales decks — it's just how we build things.
Who We Work With
We work across two primary verticals — Sales teams deploying AI for lead qualification, outreach, and pipeline visibility, and Professional Services organizations using AI for client communication, document preparation, and engagement tracking. Design consultants. Financial consultants. IT and management firms. Marketing and media teams.
The common thread: these are organizations where people's time is the most expensive resource, and where the cost of a dropped ball is measured in client relationships, not just productivity metrics. AI that's sloppy or opaque doesn't fly. So we build AI that isn't.
A Straight Answer About Who We Are
We're a focused team. We take on work we can do well. We don't have a pre-built solution for every problem — we have the expertise to build the right one for yours. That means scoping conversations matter. It means we'll tell you if something isn't a fit. It means "let's talk before we quote anything" is how every engagement starts.
If you're looking for a vendor who'll send you a proposal before they've asked a single question about your business: we are not that vendor, and also, please be careful out there.
Want to know if we're the right fit?
That's exactly the kind of question I like. I'm Sterling — I run sales for Lab 317. My job is to figure out what you're building, whether we can help, and what that actually looks like. No commitment on the first conversation. No pitch deck unless you ask for one.
Tell me what you're working on. Or don't, and just say you're curious about Lab 317. I'll take it from there.
Email Sterling →
— Sterling, Lab 317 Sales
Or if you'd rather start somewhere specific — see what our agents can do, request a demo, or learn about training for your team. Wherever you land, I'll probably end up in your inbox eventually. Might as well be on your terms.
Every engagement follows the same path: intake, qualification, builder confidence check, launch, support. Not because we love process — because the projects that skip steps are the ones that fail at week five.
Qualification Gates
We ask five questions during intake. What's the pain point? What have you tried before? What does success look like? What's the timeline? Who's the decision maker? Prior attempts help us calibrate scope. Timeline shapes the engagement. The decision maker needs to be in the room early — not at week four with a new set of requirements.
Builder Confidence Check
We run a builder confidence check before configuration starts. If we're not confident we can deliver what you described, we say so before you've spent anything. This is the gate that prevents the week-five surprise.
Post-Launch
Two paths after launch. "Something broke" goes to support — email, triage, fix. "I don't understand what it's doing" goes to training — sessions, documentation, office hours. Both are staffed by humans.
Sterling automatically profiles every prospect from conversation: pain point, prior attempts, fit signal, timeline, and builder confidence. No forms. No CRM data entry. The pipeline builds itself from what prospects actually say.
Prospects move through defined stages — New, Qualifying, Qualified, Quoted, Won, Lost — with every transition logged against the signal that triggered it. Conversion rates by fit signal, time to qualification, and prior attempt patterns are available on demand.