Plainsman Labs helps established teams evaluate, build, and operate AI responsibly — AI readiness audits, targeted automation, and agentic workflows that ship without betting the farm on hype.
const engagement = await Plainsman.run({ phase: 'readiness', team: yourCompany, scope: ['workflows', 'data', 'risk'], guardrails: { humanInTheLoop: true },}); // → AI-BOM.pdf delivered// → 3 shipped automations live// → 1 agentic workflow guardrailed✓ Your team, still in charge.
Each pillar maps to a concrete engagement — so you always know what you are buying and what “done” looks like.
Every engagement starts with the work your team already does — mapping real processes, identifying leverage, then applying AI only where it is safe, defensible, and measurably better.
Workflow mapping, data readiness, and an AI bill of materials (AI-BOM) so leadership can see exactly what is possible, what is risky, and where to start.
Ship automations that replace the dull, repeatable, error-prone work first — wired into the tools your team already uses.
Systems that plan, act, and report back — with guardrails, observability, and a clear off-switch at every step.
A deliberately small, senior engagement — no armies of juniors, no vendor gravity. You end with working systems and a team that understands them.
Map the real workflows, interview the people doing them, inventory data and tools.
Score use-cases by business impact, implementation risk, and data readiness.
Prototype, iterate, and harden the top-scoring workflows with human checkpoints.
Document, hand off, and stand up evaluation so quality is measured, not assumed.
These are not marketing lines — they show up as clauses in the SOW (Statement of Work), DPA (Data Processing Agreement), and AI-BOM (AI Bill of Materials) delivered with every engagement.
Your data is never used to train third-party foundation models. Period. Written into the Data Processing Agreement.
A living bill of materials lists every model, API, prompt, and tool powering what we ship — so audits, swaps, and cost reviews are trivial.
Scope, timeline, and deliverables defined up front. Change control is explicit — no silent scope creep, no open-ended retainers.
An AI Readiness Audit is a structured engagement where we map your team’s real workflows, inventory your data and existing tools, and score AI use-cases by business impact and implementation risk. You receive an AI Bill of Materials (AI-BOM) and an executive-ready roadmap — so leadership can see exactly what is possible, what is risky, and where to start.
Engagements run on a 90-day arc: Discover → Prioritize → Build → Operate. All scope, timeline, and deliverables are defined up front in a fixed SOW. No open-ended retainers, no silent scope creep.
No. Every engagement includes a no-training guarantee written into the Data Processing Agreement (DPA): your data is never used to train third-party foundation models. Period.
An AI Bill of Materials (AI-BOM) is a living document that logs every model, API, prompt, and tool powering what we build. It makes audits, model swaps, and cost reviews straightforward — and is delivered with every engagement so your team stays fully informed.
Plainsman Labs works best with established teams at mid-market companies who want to move past AI pilots and ship real, defensible automations. Engagements are deliberately small and senior — no armies of juniors, no vendor lock-in.
You end with working systems your team understands: at minimum three shipped automations, one agentic workflow with guardrails, an AI-BOM, and documentation designed for handoff. The goal is a self-sufficient team — not an ongoing dependency on us.
Send a short note about what you’re working on and we’ll reply within one business day to see whether an AI Readiness Audit is the right fit.