Where AI shows up in the work.
From finance and operations workflows to private knowledge and policy agents to full operating-model redesign, these are the areas where AI shows up in how your business actually runs. Each ships on the same delivery model: process redesign first, data architecture next, AI for impact. Most engagements start with one; when the highest-impact opportunity is specific to your business or industry, we build that too.
Built for the systems where work actually happens
Where work moves through finance and operations.
AI-Augmented Financial Close.
Reconciliations, flux analysis, and PBC prep handled by agents so the close runs in days, not weeks. Read the use case →
Expense & Labor Reconciliation.
Match high-volume expenses and paystubs against records each cycle, with people only on the exceptions. See the case study →
AI-Driven Order-to-Cash.
Dispute resolution, cash application, and invoice accuracy to free working capital. Read the use case →
AI-Driven Procurement & Spend.
Spend analysis and intake-to-approval that surface savings before dollars leave the business. Read the use case →
Ranges reflect typical mid-market outcomes and are not guarantees. Actual target metrics are selected in week 1 based on baseline data, executive priority, workflow feasibility, and implementation complexity.
Expert knowledge work, private and cited.
Policy & Knowledge Agents.
Private agents that read your policies, regulations, and playbooks and answer with cited, explainable references, the reasoning a specialist would do, in seconds. They power PAPAIA for FEMA Public Assistance, and extend to healthcare, financial services, and state & local government. See Private AI →
Document & Email Agents.
Read and process documents and email at scale, hundreds of pages in seconds, extracting, classifying, and drafting with traceable citations, entirely inside your environment. See Private AI →
The foundation AI stands on.
AI-Readiness & Operating Foundation.
Map how work actually moves, surface the bridges people are quietly maintaining, and build the operating foundation an AI rollout can credibly stand on. See the case study →
AI-Native Operations Design.
Redesign the operating model with AI as a participant, not a bolt-on feature, process and decision rights rebuilt around what agents can reliably do. See the case study →
The methodology applies to everything we build.
Same delivery model on every engagement: process redesign first, then ERP and data architecture, then AI. Outcome ranges reflect industry benchmarks calibrated to that delivery model. Actual results vary by organization baseline, data quality, change-management discipline, and the strength of executive sponsorship.
We redesign the process (our 3-step method), target one of four EBITDA levers, in the system where the work actually lives, delivered as a 5-week Sprint or a 12–16-week Buildout.
Process redesign first.
Anywhere humans are quietly bridging gaps that the system should bridge, AI will fail. We start by making the implicit explicit: workflow mapping, decision rights, handoff artifacts.
ERP & data architecture next.
AI agents can only be as reliable as the data they consume. We build the consistent, governed data layer that most mid-market companies don't have.
AI for impact.
AI is the leverage layer on top of a redesigned operating model, not a replacement for the design work. Private, optionally air-gapped agents that respect IP and audit obligations.
How they sequence across a value creation plan.
Start with one operating workflow.
A CFO-led workflow like financial close or expense reconciliation proves the model fast, on data and process the rest will reuse.
Layer in a knowledge or document agent.
As the data foundation matures, private knowledge, policy, and document agents compound on the work done early.
Compound at mid-hold.
By mid-hold, additional use cases compound on the data and process work done early. The organization becomes its own AI shop.
Pick what fits.
Not sure where to start, or have something custom?
Discuss a 5-week Sprint. In five weeks, we'll select, design, and prototype the highest-impact workflow, proven workflow or custom agent, and leave you with a rollout plan and a fixed-scope build proposal. Some clients continue into a larger buildout; others leave with the prototype, roadmap, and internal decision package.
Discuss a 5-week Sprint →