FarPoint adds AI reasoning workflow development

FarPoint now offers AI reasoning workflow development as part of AI Evaluation & Red-Teaming. The service gives teams a way to commission a defined revision to an assistant used for research support, internal decisions, or drafting, then evaluate how that revision performs.

An evaluation may reveal a recurring problem that deserves more than an isolated correction. An assistant might recommend an option before learning the decisive requirement, turn an ambiguous description into a confident claim, or lose an important qualification when shortening a message. The development engagement starts with the task and the behavior the assistant needs to exhibit.

We work with the client to define the application, the questions it should answer, the evidence available to it, and the circumstances that call for clarification or human review. Those requirements guide the agreed workflow revision or prototype. A follow-up evaluation then examines the revised version in selected scenarios, recording successes, remaining failures, and tradeoffs.

Deliverables can include a behavior specification, a working prototype or workflow revision, an evaluation report with concrete examples, and handoff documentation. Implementation responsibilities, access, and reuse terms are agreed before the engagement. The findings describe the conditions tested; they do not establish error-free behavior across other tasks or settings.

The offering also connects with FarPoint's Legal Engineering and Practical AI Governance work. Where an assistant supports a process governed by legal or policy requirements, client counsel supplies or approves the legal interpretation, while the client retains policy and operational decisions. The engagement can turn those agreed requirements into a workflow and provide evidence for the team's review of it.

FarPoint's Epistemic Alignment Distillations project provides a development example. Its portfolio shows recorded responses from fictional scenarios, alongside results and limitations from a synthetic evaluation. It is a starting point for discussing the behavior a client needs and the evidence an evaluation should produce, rather than a prediction of performance in a new application.

Teams interested in developing an assistant workflow can contact Andrew Nordick to discuss the application, recurring problems, and intended outcome. The initial conversation establishes what a focused engagement would need to address.