Proof, one engagement
at a time.

Three merged entities, hundreds of payer contracts, and no formal contract system or negotiation engine. A two-person team ran the payer lifecycle on PDFs and spreadsheets, with revenue leaking through missed negotiation windows, passed renewals, and reimbursement schedules the team could not reconcile against each contract.

The payer book they already had: 1,000+ agreements across drives, boxes, and laptops. Revenue cycle, operations, and finance set the operational priorities, with SharePoint as the primary repository. The client keeps the repository, the renewal matrix, and the final say at every checkpoint.

Two healthcare lines of business standing up at once: surgical asset tracking with a large device maker and three of its agencies, and a state emergency-preparedness supply platform. About 12 recorded meetings a week with health systems, device companies and state and federal agencies, and teams that had never run a program this size. A traditional PMO would add 1 to 3 staff per workstream and still miss the cross-functional risk.

Six workflows stood up on the tools the team already ran: recorded meetings in Granola, Notion for tasks, decisions and risks, and the Claude desktop app. The PMO lead owns exceptions and the risk register. Every human correction is written back into the prompts.

Up to 40% of users picked the wrong insurance plan and 7% could not find theirs, driving cancellations, provider churn, and missed revenue. Underneath, a decade-old database of ~12,000 plan records patched by manual research, offshore teams, and outside vendors.

The data-operations team moved from manual maintenance to high-judgment review. Product, operations, engineering, and data took the handoff with taxonomy, SOPs, and training, on the systems they already ran: their internal proprietary database and data lake, and the Microsoft suite. The growth came from data the business already owned.

A proven logistics, inventory, and supply-chain platform, redesigned and deployed for healthcare: statewide emergency preparedness and readiness across 8 regional coalitions, 8 health systems, and 2 state departments. Federal expansion is the long-term goal.

The client's existing platform carried the work, adapted rather than rebuilt. State health and technology departments, coalitions, and health systems align on one operating picture. We stayed on as the fractional AI arm, applying AI principles and practices to the system they already run.

Provider-market dominance, and a board mandate to take a risk adjustment product into payer segments the commercial team had never sold to. Started from no payer value proposition and no target list, in a crowded and maturing market.

Built around the client's own product, growth, and sales teams, with 15 voice-of-customer interviews reached through the 3Pillars network, VP to board level. The sales team kept and shaped the growth enablement kit; the board approved the roadmap.

Senior officers spent 30 to 45 minutes on every case review, and situational awareness was assembled by hand, district by district, hours late. Modernization had to happen inside the government's own environment.

The state's existing infrastructure and camera estate, kept: video intelligence runs above installed CCTV without replacing it. Officers' corrections retrain the models, and command reviews every flag.

AI that reads aortic hemodynamics from the CT and MR scans hospitals already take: a 1,700+ patient study in Radiology, four pilot academic medical centers, an FDA 510(k) pathway confirmed, and no commercial function or budget to hire one before a seed raise. The unknowns were the economic buyer, the price, the implementation burden and the defensibility.

Founders with clinical standing, warm relationships at the pilot sites, and the published evidence. 3Pillars runs sales and business operations as a fractional team; company leadership keeps every decision.

A large corpus of Medicaid, Medicare and state public health data with no utilization or pricing layer: what the state's residents actually use and what it costs. The plans publish their negotiated rates, but the files run 5 to 200 GB each and 100 million+ raw rows statewide.

The corpus, the public health mission and a business plan with seven customer types from public good to paid. The client paid for the initial specification; 3Pillars delivered beyond it, and the client needed no software of its own.

About 2,130 open memos and $15M+ of consigned inventory in a vendor-hosted ERP with no API, ~$2M past due across 234 accounts, customer data split across the ERP, the CRM and the inbox, follow-ups written one at a time, and a CRM nobody trusted: fewer than 1 in 2,000 records had a valid owner.

The data, locked in the ERP, and 16 outbound reps across the US and India who knew their accounts. A person approves every follow-up before it sends; the client keeps the final say.

No AI capability anywhere in the firm. Data rooms read by hand too late in the deal window, about 750 proprietary targets sitting unworked in a stale CRM, 200+ limited partners tracked in spreadsheets, and partners who disagreed on what AI was worth.

The deal CRM with 35,000+ interaction records, placement-agent and Outlook history, and the data rooms. The investment committee ratified the AI charter; the partners now build their own Claude skills.