Strategy. Capability. Execution.
3Pillars.ai builds value-creating AI inside mid-market companies. A senior operator who has run businesses like yours embeds in your organization and builds the capability with your team. Priced for the middle market.
Every AI use case, ranked by the number it has to hit.
| Use case | Stage | Status | Number to hit | Progress |
|---|---|---|---|---|
| Contracting engineRevenue & contracts · 6 agents | In production | On track | $2.0M+ | 92% of the way |
| Pricing integrityRevenue & contracts | Scoping | Data ready | $700K | not started |
| Order intake triageOperations · 3 agents | In pilot | On track | $640K | 58% of the way |
| Quote & proposal deskRevenue & contracts | Selected | Gate 1 passed | $410K | 14% of the way |
| Management officeOperations · 2 agents | In production | Target beaten | 1-3 FTE | target beaten |
Where the value sits across the business. Darker tiles carry more annual value.
An agent checks each incoming order against the contract and the item master, and sends only the exceptions to a person. Week 4 of 6; the scale decision comes at week 6, with proof in hand.
Every dollar traces to a case. Reconciled with Finance monthly.
| Month | Cases | Credited | Plan | Against plan | Running total |
|---|---|---|---|---|---|
| March | 188 | $86K | $150K | −$64K | $86K |
| April | 310 | $142K | $150K | −$8K | $228K |
| May | 457 | $210K | $150K | +$60K | $438K |
| June | 579 | $265K | $150K | +$115K | $703K |
| Year to date | 1,534 | $703K | $600K | +$103K | $703K |
The models work. What fails is organizational: wrong use case, no number, no owner. And in the mid-market, every stalled pilot is somebody’s real budget.
Most AI programs die in the seams between the strategy firm, the risk committee, and the build vendor. We closed the seams: deep strategic knowledge from our experts, capability built and embedded within your organization, and execution your P&L can carry.
A map of your operation with every AI use case valued for ROI and scored: moat vs commodity, complex vs simple. The view that helps us determine value-creation opportunities.
The organizational harness. A senior AI professional embedded in your team, accelerating AI. From governance to prototyping, this is where value compounds quickly.
Priced for the mid-market. Our own build team with agents underneath, working in your environment. You own the code, the playbooks, and the results.
Works inside your business. Finds where the value lives, sizes it, and minds the risk from first map to production. Industry judgment, and the call on when AI is not the answer.
Build with us, run the pilots, and own the tools and playbooks at the end. The capability grows inside your organization and stays there.
Production engineering priced for the mid-market, with AI agents underneath. No pyramid of juniors on your invoice.
A senior operator joins your team and spends weeks inside the actual workflows, learning how the work gets done: the processes, the data, and the people who own them.
Built from inside the work: every use case mapped, valued for ROI, and scored on one grid. A number on every opportunity. Most don’t survive the scoring.
We build the pilot against the number. For qualified opportunities, the first working demo is on us.
Only proven work reaches production. The build team builds it, the capability takes root with your people, and you own what we build.
You see it working on your use case before you commit a dollar to the build.
If the pilot misses the number, it does not scale. You decide with proof in hand.
The system, the code, the playbooks. In your environment. No subscription to cancel.
Health plan advisors who deploy AI, starting from this year's payer agenda.
AI that moves all three drivers of return: EBITDA, the multiple, and the clock.
More service per appropriated dollar, with the audit trail built in.
Marketing at machine speed, operations that keep the promise.
AI that lifts throughput and margin, from the plant floor to the supply chain.
The thinking behind these pages, across every vertical, lives in Our insights →
Stood up, put into production, and reading more than a thousand payer contract documents. $7M identified across the book; contract operations from 40+ hours a month to 8.
A core data model and its workflows, redesigned and run by seniors on the engine rather than an associate bench.
Two full-time coordinator roles of effort, run by agents instead. Roughly $300K a year in loaded cost, taken out of the back office.
1,000+ contracts processed; $7M identified.
Terms, benchmarks, and leakage surfaced from your own paper.
First drafts from your win history, on your templates.
Buyer briefs and account theses, assembled on demand.
Deals and contacts gone quiet, ranked and revived from your own CRM history.
Aging invoices chased with drafted, personalized outreach and a memory of every promise.
Review time from 30 to 45 minutes down to 5 to 10.
Document-heavy workflows with a number attached.
Summarization, routing, next-best-action.
Vision models extracting and validating records.
Thousand-file rooms read in full, with the red flags surfaced weeks earlier.
Up to 40% of foundational architecture, pre-built.
Open-source models inside your environment, safe for regulated data.
Meeting capture to board materials, on cadence.
Tracking that proves value and keeps it compounding.
What your best salespeople and technicians know, captured and answering on live calls.
Including us. The answers separate a system in production from a science project. We publish ours because we like them.
| Strategy consultancyadvises | 3Pillars.aidesigned for all three | AI build shopbuilds | |
|---|---|---|---|
| Who finds the use case? | Analyst benchmarks and stakeholder interviews. | An operator embedded in your business maps the work from the inside and attaches a number to each opportunity. | You bring it. They build what you ask for. |
| What number is it accountable to? | A business case inside the deck. | A number to hit, set before anything is built. Reconciled monthly after it ships. | Time and materials. Effort, not outcome. |
| Will it survive security, compliance, and audit? | Recommended in a governance workstream. Someone else implements. | Built in from day one. Security, risk, and compliance are part of the design, because we work where review is unforgiving. | Where pilots go to die. |
| Who owns the system? | There is no system. There is a roadmap. | You do. Your environment, your code, your playbooks, and your people trained to run it. No subscription. | Their platform. You rent the outcome. |
| What happens when AI is the wrong answer? | Another phase to study it. | We say no, with the analysis that shows why. Knowing when AI is the wrong answer is most of the judgment you’re hiring. | AI is always the answer. They sell AI. |
Bring these questions to every pitch you sit through, including ours. Our answer is usually a working demo.
“Our competitors are AI companies, applied to your industry. We are your industry insiders, applying AI.”
Straight answers. If yours isn't here, let's talk.
Every engagement starts with the same step: a senior operator inside your business, building the AI Leverage Map from the inside. It ends with a ranked map and real numbers, whether or not we go further together.
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