AI development for government and higher education.
We design, build, and deploy AI systems for federal agencies, state and local governments, and colleges and universities. Each one includes audit logging, documentation of how it behaves, and a review step before anything reaches the public.
Three areas of work
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Custom AI applications and agents
Assistants, agents, and document tools that work from your organization's own content and connect to the systems your staff already use.
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Data, analytics, and automation
Data pipelines, dashboards, forecasting models, and automated workflows for program, outreach, and enrollment data.
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AI strategy and governance
Use-case discovery, readiness assessments, risk reviews, and AI policy for organizations that need to justify how they use AI.
Where AI helps government teams
Most first projects take a task staff already do by hand, many times a week, and make it faster without taking the decision away from them.
Document intake and processing
Extracting, classifying, and routing forms, applications, and correspondence.
Constituent and student assistants
Answering common questions at any hour from approved content, with handoff to staff.
Internal knowledge tools
Letting staff search policies, procedures, and case history in plain language.
Reporting automation
Turning program and campaign data into stakeholder reports on a schedule.
Forecasting and prioritization
Predicting demand and flagging risk so limited staff time goes where it is needed.
Plain-language rewriting
Converting dense policy and program text into copy that meets the Plain Writing Act.
From workflow to working system
Discovery
We map the workflow, the data, and the constraints, then choose the use case with the clearest payoff.
Prototype
A working version on real or representative data, early enough that stakeholders can react to something concrete.
Hardening
Security review, evaluation against test cases, audit logging, access controls, and checkpoints for human review.
Deployment and handoff
Production deployment in your approved environment, with documentation, staff training, and source code you own.
What every system includes
These apply to every project, so your contracting, security, and compliance staff know what they are approving before work starts.
Human review
A person reviews public-facing AI output before it is released.
Documented behavior
Each system ships with a plain-language description of what it does, what it does not do, and how it was tested.
Audit logging
Inputs, outputs, and reviewer decisions are logged and can be retrieved.
Data ownership
Systems run in the environment your security team approves. Your data is not used to train third-party models.
Portability
You own the code, prompts, and documentation, and the underlying model provider can be changed.
Framework alignment
Designed around NIST AI Risk Management Framework concepts and current OMB guidance on federal AI use and acquisition.
Accessibility
Interfaces meet Section 508 and WCAG 2.1 AA.
Michael Rarick, President
Michael is a doctoral candidate in Artificial Intelligence (DBA) at Guglielmo Marconi University and holds an MBA in Data Analytics. Before founding Bison Federal Group he led AI strategy at an AI-powered telehealth platform.
We also use what we build. The opportunity screening and proposal pipeline behind our own federal and state business development runs on systems we designed in-house, and we build client systems the same way.
Because we also run campaigns, we can connect a recruitment or enrollment campaign directly to the assistant, intake form, or follow-up workflow that handles the response, and report on both in one place.
Tell us about a workflow that takes too long.
Describe the process and the data involved. Within one business day we'll reply with a suggested first use case and what a prototype would involve.