From restaurant margin math to AI agent governance — here's what's actually underserved.
Operations is boring until it isn't. Then it's the thing that's quietly bleeding your customers dry, or the thing that gets you fired when the agent ships a regression nobody can explain. The five ideas below sit in that uncomfortable middle ground — real pain, underserved markets, and enough complexity that a motivated solo founder with good tools can build a meaningful head start before the big players notice.
I've ranked these from good to great. All five are worth building. The ones at the top are just harder to kill.
Every restaurant owner knows DoorDash is probably losing them money. Almost none of them know exactly how much. The Order Channel Profitability Analyzer exists to close that gap: pull in order data across every channel, add up the real costs (platform fees, packaging, incremental labor, the whole thing), and tell the operator what their actual margin is per order, per channel, per month.
The market signal here is real. Restaurant forums are full of operators doing this math by hand on spreadsheets, getting different answers each time, and making decisions based on gut feel. Toast and Square have the data but no incentive to surface how badly third-party delivery is hurting their customers — DoorDash and Uber Eats have even less. That leaves a genuine gap for something built purely on the operator's side.
The honest risk is the "job done" problem. An operator figures out DoorDash is losing them $2 per order, raises their prices, and cancels. You've solved their problem in 30 days. The retention case rests on benchmarking — showing operators how their margins compare to similar restaurants nearby — but that requires critical mass before it delivers value. The API access risk from the platforms is also real and not fully solvable. This one lands at number five not because the idea is weak but because the retention mechanics need more work than the plan acknowledges.
Something shifted when AI coding tools got good enough to produce code that looks fine and fails in production. Vendors noticed. The result is enterprises paying $500K for a software delivery and having no defensible way to reject it — or even to know what they received.
The Third-Party Vendor Code Audit platform sits at a workflow position that nobody currently owns: the vendor acceptance gate. Security scanners like Snyk and Veracode are built for internal dev teams. SonarQube gives you a dashboard. Neither of them produces a document a procurement team can attach to a contract dispute. That's the actual job to be done here, and it's legitimately underserved.
The AI-slop detection angle is the headline, but it's also the part that needs the most care legally. Telling a vendor their code is AI-generated without a court-tested standard for what that means is a fast way to a defamation claim. The smarter play is to lead with security CVEs, test coverage, and dependency risk — the boring stuff that holds up in an audit — and treat AI-pattern signals as a quality indicator, not an accusation. The per-audit pricing model also creates a real tension with recurring revenue, but it's the right way to get started. Five paying customers at $299 each is worth more than a year of sales cycles.
Every large tech company is running the same experiment right now: cut senior roles, hire AI-native juniors, assume productivity holds. Almost none of them are modeling what happens in year three when the management pipeline is empty and attrition starts compounding. The Workforce Planning Simulator for AI-era Hiring is the tool that shows CHROs the scenario they're not thinking about.
This one is harder to build than it looks, and the difficulty is mostly epistemological. You're selling confident-looking predictions about talent outcomes 3-5 years out, based on benchmarks and educated assumptions. If a customer follows your model's recommendation and the opposite happens, the word spreads fast in CHRO networks and it spreads quietly — no angry blog post, just canceled contracts and a reputation problem you can't see coming. The validation approach matters a lot here: the manual pilot model (charge $2,500 for a human-delivered report) forces you to be honest about what the model actually knows before you let it run unsupervised.
What makes this genuinely interesting is the timing. Every major tech company is making these restructuring bets simultaneously, which means the talent consequences will also land simultaneously. The HR leaders who modeled it in 2025 will be visibly better positioned in 2028 than the ones who didn't. That's a compelling story for the right buyer, and the right buyer — a VP of Workforce Strategy at a company that just announced layoffs — is not hard to find. They're all over LinkedIn, and they just made a public announcement about exactly the decision this tool addresses.
There are roughly 24,000 MSPs in North America and Europe managing at least one client running Windows XP, Windows 2003, or an ancient SCADA system that cannot be updated. The enterprise OT security vendors — Claroty, Dragos, Nozomi — won't serve them. The pricing doesn't work, the complexity doesn't work, and frankly the sales cycle doesn't work. So these MSPs are doing nothing, or doing something inadequate, and their clients are sitting exposed to exploits like EternalBlue that have had working signatures for years.
The Network Virtual-Patch & Isolation Appliance for Legacy Servers is a cloud-managed IPS appliance with pre-built rule templates for EOL Windows CVEs and SCADA protocols, operable by a tier-1 technician, with native ConnectWise and Datto integration. The "operable by a tier-1 technician" part matters more than anything else in that description. Enterprise OT security requires dedicated security engineers. MSPs don't have those. A product that requires an OT PhD to configure is not a product for this market.
The liability exposure on critical infrastructure is a real risk and not one to wave away. A failed virtual patch on a water utility SCADA system is a company-ending event for a bootstrapped startup. The contract language, E&O insurance, and positioning as a compensating control (not a replacement for existing defenses) all need to be in place before you talk to a hospital or utility. That said, most MSP legacy clients are manufacturer shop floors and small municipal networks — real stakes, but not the same liability surface as a hospital. The idea ranks at number two because the moat is genuinely hard to replicate: telemetry across hundreds of MSP deployments builds a proprietary dataset of lateral movement patterns in legacy environments that no enterprise vendor with 50 Fortune 500 customers can match.
Here's the situation: engineering teams are running AI coding agents that open PRs, update tests, and push commits. Nobody has a clean answer to who is responsible when one of those agents ships a regression. The audit trail is a LangChain script log nobody can read. The governance is vibes.
The Agent Orchestration & Governance Platform is a GitHub App that intercepts agent-authored PRs, enforces human approval gates at configurable points, routes decisions to the right person via Slack, and generates a signed, immutable audit log of every action. That audit log is exportable for SOC2 evidence. That last part is what makes this number one.
The GitHub-will-ship-this risk is real and worth taking seriously. Microsoft has the distribution and the financial incentive to bundle agent governance into Copilot Workspace as a branch protection rule option, and their public roadmap points in that direction. But GitHub's native tools will cover GitHub-native agents. Claude Code, Cursor, custom CI agents — those are outside GitHub's lane, and that's where a lot of the interesting and dangerous stuff is happening. The multi-platform, multi-agent governance standard is a position GitHub can't occupy without contradicting their own product interests.
What I find most interesting about this one is that the buyers are already self-selecting. The r/programming thread on Claude Code has 748 comments, and a meaningful chunk of them are engineers who just got burned by an agent doing something unexpected. They're not theoretical prospects. They got burned last week and they're already asking where the governance tools are. That's about as warm as cold outreach gets. The five design partners with credit cards on file are out there — they just need someone to ship the thing first.