95% haven't reached substantial AI value at scale.
We turn promising AI ideas into useful systems, from a local prototype to an enterprise rollout. Then we help your team put them to work.
Our team has delivered projects and training for organizations including Delta, MassMutual, GunBroker.com, Sigma Thermal, Comcast, and Deloitte.
AI should make your team more capable, not more afraid.
In Gallup's 2026 survey, 18% of U.S. employees said AI or automation was likely to eliminate their job within five years. We bring employees into the rollout, give them tools for their real work, and make room for honest questions about how roles change.
Source: Gallup, Rising AI Adoption Spurs Workforce Changes
The model is only one part of the system.
A convincing pilot is not a business result. You need a clear job for AI, dependable data, a system that works beyond the demo, and people who know how to use it.
No clear outcome
The demo looks good, but no one has agreed on what should improve, who owns it, or how to tell if it worked.
Prototype to production gap
The prototype works in isolation but has not been connected to real data, safeguards, or the tools people use.
People left out
Employees are told to use AI without a clear purpose, training, or an honest conversation about how their roles will change.
Quality and cost drift
Answers, response time, and cost change after launch. Without a way to check them, the team cannot tell what improved.
We agree on what success looks like, build for the real work, and measure what changes after launch.
Build it. Bring the team. Prove it works.
AI Implementation
AI designed around a real workflow and delivered as an operational system, not a demonstration.
Learn moreEmployee AI Adoption
Practical training, clear boundaries, and employee feedback so teams can use AI with confidence.
Learn moreAI Reliability and Optimization
More accurate behavior, lower operating costs, better performance, and fewer surprises after launch.
Learn moreData and Infrastructure Foundations
Reliable data and infrastructure that allow AI and ML systems to perform consistently at scale.
Learn moreBuild the system. Bring the team. Own the outcome.
- Choose a real task or decision. Agree on the starting point, who owns it, and what should improve.
- Build and connect the right solution, from a local prototype or private deployment to an enterprise system.
- Involve employees early, practice on their real tasks, and use their feedback to improve the rollout.
Two disciplines. One accountable team.
Abisam is led by two founders who work directly with you, from the first conversation through delivery.
Tim Lafferty
Tim works on what an AI system does: whether its answers are reliable, why errors happen, and which changes make it better. His background in statistics, mathematics, and machine learning helps connect technical performance to decisions a business can act on.
Bob
Bob builds the systems AI depends on. He brings more than 20 years of architecture and infrastructure experience to data, integrations, deployment, performance, and cost. His focus is making a solution workable for the people who run it after launch.
Tim focuses on what the AI does. Bob builds the system around it. Together, they help your team put the result to work.
Notes on making AI useful.
How to Evaluate an AI Feature Before You Ship It
A pass rate is only useful when you know how many cases were tested. See how to build a repeatable baseline and report the uncertainty around it.
September 2, 2026
What to Log So You Can Debug an AI System Later
When an AI answer goes wrong, the answer alone may not show why. Record the inputs, versions, and outcome of each model call so your team can investigate.
September 2, 2026
Why Your AI Bill Keeps Climbing
Before changing vendors, find out what each AI request sends, repeats, and costs. These worked examples show where design choices can reduce spend.
September 2, 2026
Ideas we test in the open.
Phoebe Labs is where we build and share our own tools. It shows how we think through real problems, from the first idea to something people can use.
Open Shelf
Book recommendations backed by evidence pulled from real reviews. It cites its sources, unlike your last book club pick.
Visit project(opens in a new tab)In Our Image
Biblical stories read through modern psychological and philosophical lenses, with the verbatim scripture kept beside every quote.
Visit project(opens in a new tab)PlayerLots
Track your baseball sets for free, then fill the gaps with fixed-price player lots. No auctions, no haggling, no randomizers.
Visit project(opens in a new tab)Your next AI investment should have a result.
Tell us what you want to build, what is breaking, or where your team is stuck. We will help define a practical next step and how to measure progress.