AI software development — built as a project, run as a system.
Detection engines, intelligence layers, copilots, and agents that do real work inside your operation — built as a scoped software project by a team that has shipped production AI, not demos. Not the AI Office retainer: that’s a team on a monthly rhythm; this is a system with a start, a finish, and a number attached. A new AI system starts with a Validation, Design & Planning (VDP) engagement; existing systems with a System Evaluation.
We develop custom AI systems that do real work inside the operation.
AI is a competitive mandate for the middle market too — but a demo is not a system. We design and build AI software that reads, scores, drafts, and routes inside the workflows your people already run, with a person approving anything that matters. We keep up with the models so you don’t have to (we’re an Anthropic partner, and not dogmatic about it), and we use AI to build it, too. 75% fewer false positives on one detection system; ROI-positive in month one on another.
What we’re good at, specifically.
Agents & agentic workflows
Software that takes action across your systems — not just answers questions — with checkpoints where a person decides.
LLM copilots & retrieval
Language models that read your documents and data and answer from them, with citations rather than confidence. Juror profiles 3× faster for one litigation firm.
Detection & prediction
Scoring, anomaly detection, and forecasting on operational data — the AML system that cut false positives 75% with zero violations.
Data foundation & integration
AI is only as good as what it reads. The governed data layer and the integrations come with the build — and are often the actual first step.
Governance & human-in-the-loop
AI prepares. A person approves. The system logs. Designed into the architecture, not written into a policy nobody reads.
Evaluation & production monitoring
Behavior tested against real cases before and after release; accuracy and cost watched in production, not assumed from a demo.
We’ll tailor a time-tested approach to your situation.
Twenty years, hundreds of projects, the same five moves — sized to your project, never boilerplate. Every one starts with a 30-minute Discovery Call.
Shipped on this platform. Numbers attached.
12 Systems Into One AML Platform — 75% Fewer False Positives, Zero Regulatory Findings
A financial services firm consolidated 12 fragmented source systems into one audited AML data warehouse, rebuilt detection on top of it, cut false positives 75% — and passed its next regulatory examination with zero findings.
Jury Research 3× Faster for a National Litigation Firm
A national litigation firm cut jury research time by 60% and analyzed prospective-juror profiles 3× faster with an AI platform that aggregates, synthesizes, and flags what attorneys would otherwise miss.
ROI-positive in month one from freight operations intelligence
A national freight provider turned fragmented operational data into real-time intelligence — ROI-positive in the first month.
What it does for the business.
Plain language on purpose. The technical choices are ours to make well — and to explain whenever you ask. The outcomes are yours.
Does real work, not demos
Reads, scores, drafts, and routes inside the workflow your people already run — so the value shows up in the operation, not in a slide.
A person stays in charge
AI prepares. A person approves. The system logs. Anything that touches money, customers, or commitments has a human checkpoint by design.
Your data stays yours
Built in your environment, on your data. When the data can’t leave your walls, we run a private model there.
Measured, not hoped for
A KPI set in writing before the build and reported against after; accuracy watched in production, not assumed from a demo.
Become technology-driven instead of technology-frustrated.
Our no-BS, outcome-oriented approach will solve your biggest challenges and help your company do better business now.
Connect your employees, customers, partners, and suppliers to improve collaboration and gather vital insights through data.
Data & Reporting →Manage and automate your key processes or bottlenecks to drive efficiency and cost savings.
AI Office →Make smarter decisions backed by meaningful data and easy-to-use reports and dashboards. True business intelligence.
Data & Reporting →Drive innovation by discovering new revenue opportunities, monetizing data and content, and staying focused on your customer experience.
New Product Development →A platform isn’t a project. These are.
AI systems is how we build; the job is why. Pick the one that matches your situation — each starts with a priced first step.
New Product Development
An AI-native product or a system built around a model. Starts with a VDP.
Data & Reporting
The data foundation the model needs. Usually the actual first step.
AI Office
When you want a standing team shipping AI every month instead of one scoped build.
Before you call: LLM & agent comparison — which model stack fits which work · Intelligent workflow automation — the operator’s guide · Do you need a Private LLM? Six questions.
Partner, not vendor.
Frogslayer is easy to work with — they communicate in a detailed, professional manner without wasting time, and the work product is top level. They suggested an approach we hadn’t considered and built a product that works even better than we envisioned.
It’s amazing how the programmers and staff are almost melted together with our staff — it’s hard to figure out where one stops and the other begins, because they truly are a team.
Straight answers.
How is this different from AI Office?
AI Office is a team on retainer — strategy, coaching, and a build cadence, every month, for operators ready to build continuously. An AI system project is one scoped build: a defined system, a fixed start and finish, a proposal with a number. Many clients do both; the project is often how the relationship starts.
How is this different from AI Office?
AI Office is a team on retainer building automations and AI workflows on the systems you already run. An AI system project is bigger than that: a platform, a product, a detection engine. If it looks like a system, it’s a project, and it starts with a VDP.
Which models do you use?
The one that fits the task and the data requirement — we’re an Anthropic partner and not dogmatic about it. When the data can’t leave your environment, we run a private model there. The Private LLM decision tool gives you a straight read in six questions.
How do you keep an agent from doing something stupid?
Design. Anything that touches money, customers, or commitments goes through a human approval step; every action is logged; behavior is evaluated against test cases before and after release. AI prepares, a person approves, the system logs — it’s the same rule on every build.
Isn’t our data the real problem?
Usually, yes. Most AI programs that stall did so on data that wasn’t ready. That’s why Data & Reporting is often the actual first project — and why a System Evaluation is where an AI build starts when systems already exist.
Have an AI system in mind — not just an experiment?
New: a VDP validates it before you build. Existing systems: a System Evaluation. Want a team on retainer instead? That’s AI Office.