SHEP
From operating noise to a focused day.
SHEP helps leadership understand where attention is needed, why it matters, who owns the next step, and whether the result was achieved.
BOLT-ONEnhances the ERP you already run
Who doesn't want to save time and Money?
LMBR Operating System has a product named BOLT-ON. It is a complementary operating-intelligence layer for lumberyards and truss plants. It learns how your company works, surfaces opportunities, recommends the next action with the context attached, and measures what actually happened.
The current sellable starting point is a one-branch, externally read-only Shadow Pilot. Your ERP stays the agreed system of record, and BOLT-ON adds intelligence around the work without writing back.
- Your ERP remains the system of record
- Human approval on every consequential action
- Tenant- and branch-scoped isolation
- Audit history behind every AI action
The LMBR advantage
It learns your business every day
- 01Learnsyour products, language, and rules
- 02Recognizeseach customer's ordering patterns
- 03Rememberscorrections and approved exceptions
- 04Askswhen something looks missing or unclear
LMBR becomes a team member. Ordinary software knows data entry. LMBR learns how your company works, helps catch what people miss, and asks before it guesses.
What BOLT-ON is
A layer of operating intelligence that goes on top of what you run today.
BOLT-ON is not a migration, a replacement, or a rip-out. It works with authorized data from the systems you already use, learns how your company specifically operates, and adds governed interpretation, coordination, recommendation, and proof around the work.
Calibrated
It learns your company, not the industry
Your terminology, SKU aliases, product rules, tolerances, exceptions, approval paths, and correction history. LMBR learns how your branch builds a framing package.
Coordinated
It connects departments that share a problem
Sales, estimating, quoting, credit, purchasing, inventory, yard, production, dispatch, delivery, AR, AP, and management working from one version of the same job — instead of eight spreadsheets and a phone call.
Accountable
It proves what it claims
Every material action records an audit event, a recommendation entry with its evidence and rule version, and a reporting fact. Identified value and realized value are tracked as different things, because they are.
You got smarter about your business year after year. So does LMBR.
The first week, BOLT-ON is reading. It maps your products and aliases, records confidence and provenance on every mapping, and stops on the ones it is not sure about rather than guessing.
By the first month, your corrections have taught it. The hanger callout your estimator always writes a particular way stops being a question. The tolerance your purchaser applies to a lead time becomes a rule the system knows. The exception your dispatcher always overrides becomes a pattern it stops raising.
That accumulated knowledge is the asset. Calibration is company-specific and stays yours—it is the difference between software that only knows data entry and LMBR, which works as a member of your team.
The ERP relationship
Your ERP is the system of record. LMBR adds the operating-intelligence layer.
Modern building-supply ERPs are broad, capable systems that run critical transactions across quoting, purchasing, inventory, delivery, accounting, and more. BOLT-ON is designed to complement that foundation—not compete with it.
Your ERP records and processes the business. It remains the agreed system of record throughout a BOLT-ON engagement.
BOLT-ON answers a complementary question: does the system learn your operating rules, identify the opportunity across departments, recommend the action, record who decided, and prove the outcome? That loop is what we add.
What BOLT-ON adds
Dealer-specific calibration
Learns company terminology, SKU aliases, operating rules, tolerances, exceptions, and correction history.
Material-list intelligence
In the current one-branch Shadow Pilot, analyzes authorized structured product, inventory, quote, and order exports externally read-only, with source lineage and human review. PDF, photo, scan, handwriting, and OCR-to-quote intake are product vision—not offered in Shadow Mode.
Cross-functional intelligence
Connects sales, quoting, credit, purchasing, inventory, yard, delivery, AR, collections, AP, and management into one governed operating loop.
Shadow Mode
Records what LMBR would recommend, compares it with the decisions your team actually made, and proves accuracy and value before any control expands.
Savings and ROI ledger
Separates identified, validated, approved, implemented, realized, and sustained value; annualizes recurring savings and prevents double counting.
Recommendation accountability
Records evidence, confidence, expected value, approval, override, action, model and rule version, cost, and the eventual outcome.
Procurement intelligence
Combines your demand, inventory, jobs, suppliers, lead times, rebates, and cash position with market, mill, and regional signals.
Role-based coaching
Turns your actual exceptions, corrections, and operating results into calibrated coaching for sales, purchasing, yard, delivery, credit, collections, and management.
Controlled autonomy
Moves from observation, to analysis, to recommendation, to prepared work, and only then to narrowly authorized low-risk execution — at your pace, per workflow.
The whole promise
Save cash. Make more cash.
Everything else on this page is a means to those two ends. If a capability cannot be traced to one of them, it does not belong in a BOLT-ON conversation.
Save cash
Stop paying for work that should not have happened.
- Keying a list a person already typed once
- Keying quotes and orders all day
- Creating placeholders because truss software does not talk to the ERP
- Driving across the yard three times to pull one package
- Handling the same unit three times to ship it once
- Buying at a premium to cover a shortage nobody saw coming
- Waiting on another department to confirm readiness
- Chasing an exception after it has already cost the customer
Make more cash
Turn the hours you get back into selling capacity.
- Quote faster, so you are answering while the job is still live
- Quote more, because intake stopped being the bottleneck
- Hold margin, because pricing exceptions surface before they ship
- Follow up on the quotes that are actually still winnable
- Free experienced people from clerical work for customer work
- Schedule deliveries automatically instead of managing every stop by hand
- See cost-to-serve, so you know which revenue is worth having
- Collect sooner because LMBR recognizes each customer's AR payment habits
None of that is worth anything as a claim. It is worth something when it is measured against your baseline, which is what Shadow Mode is for.
Where the money goes
The expensive problems are rarely where the report is looking.
These are the operating patterns a BOLT-ON discovery tests. They are common in lumberyards and truss plants—not a claim about your company.
The quote that took two days to answer was already lost on day one.
What it looks like
- Slow response while a list is interpreted by hand
- Inconsistent reading of shorthand between salespeople
- Pricing drift and margin exceptions nobody reviews
- Senior people cleaning up ordinary requests
What BOLT-ON does about it
LMBR reads the request in the form it arrived, resolves what is clear against your catalog and rules, and asks a specific question about what is not — so the quote goes out while the job is still live.
The operating chain
Seven stages, applied to every piece of work that moves through the company.
This is the same sequence whether the work is a material list, a buy, a transfer, a load, a truss job, a credit release, or an invoice. Consistency across departments is what makes the loop measurable.
- 01
Understand
Interpret customer and vendor inputs. Normalize products, quantities, units, jobs, and requirements, and keep the original attached as evidence.
- 02
Validate
Check math, units, pricing rules, availability, permissions, confidence, credit, and exceptions with deterministic logic — not a language model's opinion.
- 03
Coordinate
Connect sales, purchasing, inventory, yard, production, dispatch, delivery, finance, and management to the same version of the work.
- 04
Recommend
Present the next action with its evidence, confidence, expected impact, accountable owner, and the approval it requires.
- 05
Execute safely
Prepare or perform only the actions you have authorized, under role, tenant, threshold, idempotency, and audit controls.
- 06
Measure
Compare the recommendation, the decision, the action, the operational outcome, and the realized financial result.
- 07
Learn
Feed corrections and outcomes back into your company-specific rules, so the next recommendation is calibrated by what actually happened here.
Stage 07 is why the sequence is a loop rather than a pipeline. What you correct becomes what it knows.
Shadow Mode
Prove it against your own operation before you depend on it.
Shadow Mode runs LMBR alongside the way you work today. It observes authorized data, identifies opportunities, produces recommendations, and compares those recommendations against the decisions your team actually made — while taking no operational action at all.
You are not asked to trust a claim. You are asked to look at what LMBR concluded about your operation, and whether it was right.
- 01Read-only
Connect safely
LMBR connects to authorized data with source lineage preserved on every record. Nothing is written back. Records that cannot be interpreted are quarantined with the reason attached rather than guessed at.
- Tenant- and branch-scoped from the first record
- System-of-record ownership and read/write boundaries agreed in writing
- Reconciliation back to your ERP so both sides agree
- 02Learning
Calibrate to your company
We teach LMBR your terminology, products, aliases, rules, tolerances, exceptions, and approval paths. Historical replay runs against a cutoff so the system is never scored on data it could not have known at the time.
- Product normalization with confidence and provenance on every mapping
- Ambiguity becomes a specific question, not a silent assumption
- Your corrections become company-specific rules you own
- 03On site
Assess the operation on site
An operational assessment at your yard or plant: how material actually arrives, gets staged, gets found, gets pulled, gets loaded, and gets out the gate — alongside how the paperwork and the decisions move.
- Material placement, staging, and travel between commonly paired products
- Where work waits, and what it is waiting on
- The handoffs between departments where ownership goes missing
- 04Spatial
Build the digital twin
Your yard or plant becomes a spatial model. Forklift and equipment movement is recorded through the shift and reconstructed into paths, corridors, dwell points, and heat maps tied to the orders being worked.
- Travel path by time of day, zone, order, and shift
- Backtracking, cross-yard travel, congestion, and dwell
- Distance per order and per material zone
- 05Simultaneous
Analyse every workflow at once
Quote, order, purchasing, inventory, yard, dispatch, delivery, equipment, and financial workflows are analysed together — because the cause of an expensive delivery is usually a decision that was made three departments earlier.
- A late credit release traced to the split load it caused
- A stockout traced to the buy that had no view of booked demand
- A redelivery traced to the readiness check nobody ran
- 06Scored
Compare recommendation to outcome
For the whole period, LMBR records what it would have recommended and when. That is then compared against the decisions your team actually made and the results that actually followed.
- How often LMBR identified the issue before the existing process did
- The false-positive and exception rate, reported honestly
- Which workflows are safe to keep read-only, prepare for approval, or narrowly automate
What Shadow Mode has to answer
- ?Where is profit leaking today, and by how much?
- ?Which recommendations were accurate and actionable?
- ?How often did LMBR catch the issue before the current process did?
- ?What is the false-positive and exception rate?
- ?Which opportunities were accepted, implemented, and realized?
- ?Which workflows are safe to automate, and which should never be?
What comes out of it
A value case built from your operation, not from an industry average.
Every figure traces to a measurement taken here, with the formula and the inputs visible, and each input labelled as something you know, something we assumed, or something nobody has yet.
- Time
- Mileage
- Labor
- Equipment wear
- Maintenance exposure
- Capacity
- Quote speed
- Inventory
- Delivery
- Cash
- Sales
What this is not
Shadow Mode is an analysis of material flow and coordination — how far a unit travels, how many times it is touched, how long work waits, and which decisions caused it. It exists to fix layout, sequencing, placement, and process. A low score is a question about the yard before it is ever a question about a person, and manager views carry the context — order mix, zones, availability, shortages, equipment assignment — that explains it.
Start with a Shadow Mode assessment.
One to three expensive workflows, an agreed baseline, and a defined success bar you set before we begin.
Digital twin
Your yard, as a model that shows you where the miles go.
Forklifts pulling orders carry an LMBR terminal, and their movement through the shift is reconstructed into paths, corridors, dwell points, and heat. Tied back to the order each trip was serving, it stops being activity and becomes material handled per mile travelled.
Yard modelIllustrative
Generated by this page. Not customer data.
Headline yard KPI
pounds pulled ÷ miles travelled
5,120
pounds per mile
- Pounds
- 9,420
- Miles
- 1.84
Both figures come from the model on this page. Your numbers come from your own recorded shifts, and a low score is read against order mix, zones, availability, and equipment assignment before it is read as anything else.
What the analysis surfaces
- Two full cross-yard runs to the same rack for one order
- Every pick returns to staging before the next is started
- Congestion where the load-out approach and the rack aisle meet
- Longest single leg is to the lowest-weight line on the ticket
Travel tied to work
Each sample links tenant, branch, forklift, device, operator session, order, line, timestamp, and location — so the question is never just where the machine went, but what it was doing there.
Weight from governed data
Pounds come from your item master or an approved derivation, never from an operator typing a guess. Where reliable weight does not exist, the line is flagged as missing rather than estimated into the KPI.
Before and after, measured
Move a rack, change a pull sequence, reassign a zone — then compare the same measure across shifts, operators, and days to see whether the change actually did anything.
Quote and order intelligence
Prove the intelligence against the data you authorize.
The current one-branch Shadow Pilot starts with authorized structured product, inventory, quote, and order exports. LMBR analyzes them externally read-only, preserves source lineage, and routes uncertainty to a person. PDF, photo, scan, handwriting, and OCR-to-quote intake are not offered in Shadow Mode.
Material interpretation
Your product rules, with a conservative exception policy
3 ready1 question
| Customer wrote | LMBR read | Qty | Status |
|---|---|---|---|
| 48 2x4x104-5/8 DF #2 | 2x4 DF #2 104-5/8 Stud | 48 | Ready |
| 16 2x6x16 PT | 2x6 PT 16' | 16 | Ready |
| 12 7/16 OSB | 7/16 OSB 4x8 | 12 | Ready |
| 4 hangers for double 2x10 | Joist hanger — model unresolved | 4 | Ask |
Clarification generated: “Which hanger model or series should we use for the double 2x10 condition?”
Illustrative list. Not customer data.
Uncertainty becomes a question, not a guess
Three lines resolved cleanly against your catalog. The fourth did not, so it stops. LMBR writes the specific question a salesperson would have asked, and the line waits for a human answer rather than becoming a plausible-looking wrong SKU that ships.
Optical character recognition carries a confidence score, and anything below your threshold routes to human verification. A document that cannot be read reliably is never quietly treated as though it were.
Why speed here turns into revenue
The clerical part of quoting is what makes quoting slow, and slow quoting is what loses jobs that were winnable. Remove the rekeying and the searching, and the same salespeople answer more requests in the same day — which is more quoted opportunity, not merely a tidier process.
Approval carries forward
When the customer accepts, the customer, job, products, quantities, notes, and pricing move into the order package. Nobody types the order a second time.
Readiness is checked in sequence
Purchase order captured, tax status confirmed, credit exposure checked, availability confirmed — in order, with the exception raised before it becomes expensive.
The record stays reconciled
Approved transactions and status synchronize with your ERP, which remains the system of record, and reconciliation runs in both directions.
Purchasing and inventory
A buy is only as good as the picture behind it.
ANNIE assembles on-hand, committed demand, inbound purchase orders, supplier lead time, the next weeks of booked jobs, cost history, rebate position, and cash timing into one recommendation — with the quantity, the supplier, the timing, and the reason attached.
MADDOX works the other side of the same problem: whether the inventory that appears available actually is. Committed, misplaced, arriving too late to help, or better sourced from another branch are four different answers, and they lead to four different actions.
Neither of them buys anything. The recommendation goes to whoever holds that authority, with the evidence visible, and their decision — including an override and its reason — is recorded against the recommendation.
ANNIE
Purchasing
- Booked demand and upcoming jobs in the same view as on-hand
- Lead time and supplier performance as data, not memory
- Cost movement against your own 30-day history
- Rebate position and cash timing considered together
MADDOX
Inventory control
- Available versus committed, misplaced, or inbound-too-late
- Excess and dead stock priced at your carrying rate
- Transfers evaluated against what the move actually costs
- Cycle-count accuracy tracked so the number is trustworthy
Rebates and vendor programs are tracked against the buying that earns them, so a program is visible while there is still time to hit it rather than discovered after the period closes.
Yard, dispatch, and delivery
The promise is only safe when the load is actually ready.
LMBR's Control Tower holds route, stop, truck, driver, readiness, proof of delivery, exception, and audit state — market-wide, across locations — rather than leaving dispatch in a tool that only sees the trucks.
Yard
YARD CONTROLPull work tied to the order it serves. Pounds, travel, touches, staging, condition, and disposition become measurable, and shortages surface at the rack rather than at the truck.
- Forklift terminals carry the pull ticket and the exceptions
- Shortage, damage, and substitution captured where they happen
- Pounds per mile as the headline productivity measure
Dispatch
DISPATCH CONTROLLoads built against readiness, weight, geography, equipment, driver availability, and the customer's window — with capacity, blackouts, and booking locks enforced rather than remembered.
- Readiness checked before a delivery is promised
- Sequencing and combining evaluated for incremental miles
- Turnaround and extra turns measured per truck and driver
Delivery
DELIVERY CONTROLThe driver carries the complete packet — address, gate code, contacts, instructions, photos — and proof of delivery, notes, and exceptions flow back into the same record.
- Proof of delivery attached to the order, not to an inbox
- Customer kept informed without a phone call to the office
- Exceptions escalated while the truck is still on site
Why a redelivery is the most expensive thing in the yard
It is the miles again, the truck again, the driver again, the handling again, and a customer who now plans around you differently. Most of them trace back to a readiness check that nobody ran or a shortage that surfaced too late — both of which are visible upstream if anything is looking.
Delivery cost, by the thing served
Fully loaded delivery cost is resolved by customer, job, order, stop, and route — so revenue that looks attractive at gross margin can be examined against what it actually costs to serve. Some of it will not survive the look, and that is the point.
Truss and component operations
A remake costs the material, the labor, the capacity, and the delivery. Twice.
LMBR connects engineered component design and production, closing the gap between what was designed, what can actually be built this week, and what was promised to the jobsite.
Most expensive truss problems are input problems. A job reaches design with incomplete or conflicting information, design time is consumed, production is scheduled, material is committed — and the conflict surfaces on the shop floor or at the jobsite, when it is at its most expensive.
The cheapest place to catch that is before design starts. LMBR checks job inputs for completeness and conflict first, so estimator and designer time goes to jobs that are genuinely ready for it.
Readiness before design
Incomplete or conflicting job inputs are identified and returned with the specific question, before estimator and designer hours are spent on them.
Production tied to delivery
Design readiness, material availability, capacity, and change orders are connected to the delivery commitment, so the build sequence reflects what is genuinely deliverable.
Remakes, variance, and downtime measured
Remake rate, material variance, labor variance, queue time, and downtime are measured against the jobs that caused them rather than summarised at month end.
A real constraint, or a coordination problem
Before another saw, table, shift, or crew is added, the analysis separates true physical capacity limits from batching, sequencing, handoff, and readiness problems that consume the capacity you already own.
Specialized by the work. Engineered components, trusses, EWP, and prefabricated wall panels are handled differently from lumber, hardware, siding, drywall, framing labor, roofs, blocking, and bracing. LMBR respects those operating differences without exposing its internal assistant design.
Your LMBR guides
Meet SHEP and ANNIE. The intelligence stays protected.
SHEP helps your team turn operating signals into clear priorities. ANNIE helps purchasing teams evaluate what to buy and why. Behind them, LMBR coordinates protected LBM intelligence across the business without exposing the proprietary methods that make it work.
ANNIE
Better purchasing decisions, with the reason attached.
ANNIE helps purchasing teams evaluate demand, availability, timing, and supplier considerations so the human decision-maker can act with better context.
Protected by design
The outcome is visible. The invention stays confidential.
Customers see recommendations, evidence, approvals, ownership, and measured outcomes. LMBR does not expose the proprietary coordination methods, internal roles, decision architecture, or calibration logic behind them.
Your control
You decide how much authority LMBR has. Per workflow. Reversible.
There is no single switch that turns the system loose. Each workflow sits at a level you set, and moving one up is a decision you make on evidence from the workflow below it. Moving it back down takes one action and needs no justification.
Recommend
Level 3 of 5LMBR proposes the next action with evidence, expected value, and an owner.
What LMBR does here
- Ranks recommendations by financial and customer impact
- Attaches evidence, confidence, expected value, and the rule version used
- Names the accountable owner and the approval the action requires
What it still cannot do
- Act on its own recommendation
- Write to any system
Deterministic validation stays authoritative
Math, units, pricing rules, permissions, thresholds, and credit checks are code, not judgement. A model may propose; it does not get to overrule a rule.
Approval is a person, not a setting
Where a workflow requires human approval, the approval is recorded against the named person who gave it — along with anything they overrode and why.
Every action leaves a trail
Material AI actions record an audit event, a recommendation entry with its evidence and rule version, an idempotent outbox event, and a reporting fact. The trail is not optional and cannot be removed.
LMBR private demo
Want to see how LMBR thinks about your operation?
Request a private demo passcode. Tell us who you are and how your team is built so we can review the request and prepare the right LMBR experience for your operation.
Step 1: Tell us who to build the walkthrough for.
Step 2: Enter how many people work in each part of your operation.
Then: The LMBR team will review your request and be in touch about private-demo access.
The value ledger
Identified value is not realized value.
Software is very good at reporting activity as though it were money. The ledger exists to stop that: a finding moves through six states, and only two of them mean anything actually changed.
Recurring savings are annualized once. A saving already counted in one driver is not counted again in another. One-time avoidable events are recorded separately from recurring ones. The discipline is unglamorous and it is the whole point.
Identified
LMBR detected an opportunity and documented the evidence.
Validated
You confirmed the issue, the baseline, and the calculation method.
Approved
An authorized person accepted the proposed action.
Implemented
The action was completed and recorded.
Realized
The operational or financial result was measured.
Sustained
The improvement held, without unacceptable side effects.
Guided demo
Click below to see how the Quote to Delivery workflow works.
Take four minutes out of your day to see how LMBR can save thousands of hours a year. SHEP narrates while ANNIE supports purchasing, and you make the approvals yourself—so you can remain in the loop while you gain trust in us.
The demo runs on illustrative data. No customer database, live ERP connection, or production record is used in it. PDF, photo, scan, handwriting, and OCR intake shown in the product vision are not offered in the current Shadow Pilot.
Twelve stepsGuided or explore freely
- 01StartWhat BOLT-ON is
- 02IntakeProduct vision—not in Shadow Mode
- 03InterpretResolve, or ask
- 04QuotePrice, margin, availability
- 05ApprovalPO, tax, credit, readiness
- 06ANNIEThe buy, with its reason
- 07DispatchTruck, route, sequence
- 08YardPounds per mile
- 09DeliveryPacket and proof
- 10ARClean billing handoff
- 11ShadowScored against what you did
- 12CommandThe operating picture
Why it works this way
Built by someone who has actually run the yard.
LMBR is built by Kenny Mays, who has spent more than 27 years in lumberyard and truss-plant operations. SHEP, LMBR's lead AI, asks your customer a direct question whenever he is not certain—helping ensure that customers receive exactly what they intended to order.
A traditional ERP stores the data it is given; it does not know whether that data is correct, incomplete, or inconsistent with the customer's normal buying pattern. LMBR learns the business and recognizes those patterns. It can ask Mr. Builder, “You usually order 12d nails with a framing package. Do you need any?” The customer confirms the answer before the order moves forward.
That is the difference between merely recording an order and helping the customer get the right order. LMBR brings industry knowledge, customer history, and human confirmation together before a preventable mistake reaches the yard or jobsite.
We are not asking you to throw out your ERP. We are asking whether the business is measuring what its current systems are not making obvious.
“As we built LMBR, every decision came back to two goals: make LMBR feel like a team member, not just another system—and build something the LBM industry has never seen before.
I believe we accomplished both.”
Kenny Mays · Founder, LMBR
Kenny Mays
Founder, LMBR
27+ years in LBM
27+
Years in LBM
Lumberyards and truss plants, not software companies adjacent to them.
1
LBM operating system
Calibrated to the customer's people, rules, equipment, and workflows.
Written for the people who do the work
- Estimators
- Salespeople
- Purchasers
- Yard teams
- Dispatchers
- Drivers
- Truss designers
- Production
- Credit and AR
- Accounting
- Managers
- Owners
A dispatcher and a credit manager do not want the same screen, alert, or priority. LMBR adapts the experience to the person doing the work without exposing its internal design.
Security and governance
The controls are the product, not a page in the contract.
An intelligence layer that reaches across every department is only acceptable if the boundaries are real, enforced in code, and visible to you. Here is what is actually built in.
Tenant and branch isolation
Data is scoped to your organization and branch at the model layer, so isolation is a property of every query rather than a filter someone remembered to apply.
Centralized authority
Permissions resolve through one authority module. There are no scattered role checks drifting apart across features, which is how permission bugs normally happen.
Deterministic validation
Math, units, pricing rules, thresholds, and eligibility are code. A model can propose an action; it cannot talk its way past a rule.
Human approval gates
Consequential actions stop at a named person. The approval, the override, and the reason are recorded against the recommendation they belong to.
Audit history on every AI action
Material AI actions record an audit event, a recommendation entry with evidence and rule version, an idempotent outbox event, and a reporting fact.
Source lineage preserved
The original request — the email, the photo, the spreadsheet — stays attached to the work it produced, so any interpretation can be checked against what arrived.
Read-only by default
A BOLT-ON engagement starts with no write path to your systems at all. Any write is a boundary you open deliberately, for a named workflow.
Quarantine over guessing
Records that cannot be interpreted reliably are quarantined with the reason. Confidence and provenance are recorded on every product mapping.
Reversible by design
Authority granted per workflow can be withdrawn per workflow, immediately, without an engineering change or a support ticket.
On claims. This page does not assert a security certification, a compliance attestation, a service-level guarantee, or a contractual date. Where you need one of those, ask for it directly and we will tell you its actual status rather than implying it here.
Getting started
A path where every step has to earn the one after it.
Your team keeps working the way it works. Nothing about the early stages requires a process change, a data cleanup project, or a system migration first.
- 01
Select the expensive workflows
One to three problems with meaningful financial or customer impact. Not a platform rollout — a specific, provable question.
- 02
Establish the baseline
Agree the data sources, owners, definitions, time period, formulas, and exclusions before anything is measured, so the result cannot be argued with afterwards.
- 03
Connect safely
Define system-of-record ownership, read and write boundaries, permissions, tenant controls, retries, and reconciliation. Read-only to begin with.
- 04
Calibrate LMBR
Teach it your terminology, products, aliases, rules, exceptions, tolerances, and approval paths. Historical replay runs against a cutoff so it is never scored on hindsight.
- 05
Run Shadow Mode
LMBR runs alongside the operation, recommending nothing into production, while accuracy, opportunity, and risk are measured against what your team actually did.
- 06
Review the value ledger
Separate identified, validated, approved, implemented, realized, and sustained. Decide what you believe.
- 07
Expand only where proven
Add workflows, locations, users, and controlled automation on the evidence — at the pace you set, not a schedule we set.
The decision in front of you is not whether to replace your ERP. It is what LMBR has to prove using your own data.
Start at step one
The hard questions
The objections worth raising, answered without the sales gloss.
If one of these is the reason you would say no, it is better raised now than three meetings in.
It very likely performs the transaction, and we are not going to tell you otherwise. The question is a different one: does it learn your operating rules, identify the opportunity across departments, recommend the action, record who decided, and prove the outcome afterwards? BOLT-ON is built to add that loop around the system you already run.
That is exactly why we lead with BOLT-ON. Your ERP stays the agreed system of record. LMBR adds interpretation, coordination, intelligence, and measurement around it. Nothing about a BOLT-ON engagement requires you to move your system of record.
Worth asking: which ERP workflows create the most manual work or the least visibility?
Dashboards show what happened. LMBR is built to say what should happen next, who owns it, what it is worth, and whether the action produced the result. The difference is the closed loop, not the chart.
Worth asking: what happens in the hour after a dashboard reveals a problem?
Neither do we, without proof and explicit authority. BOLT-ON starts in observation. Deterministic validation and human approval stay authoritative, and you decide — per workflow — whether LMBR may observe, analyze, recommend, prepare work for approval, or act inside limits you set. You can move any workflow back down at any time.
Worth asking: which actions should stay read-only, which are safe to prepare for approval, and which should never be automated?
The difference is not a chat box. It is calibration to your company specifically, a coordinated set of LBM specialists rather than one general assistant, Shadow Mode proof before authority expands, recommendation accountability with evidence and version history, and a value ledger that separates identified from realized.
Worth asking: which decisions need better evidence, ownership, or cross-department coordination?
Most are not, and LMBR is built for that condition rather than around it. Records it cannot interpret are quarantined with the reason, not guessed at. Ambiguity becomes a specific question. Calibration is the process of teaching LMBR your aliases, tolerances, and exceptions — the mess is the input, not a prerequisite.
Worth asking: which product, customer, or job data causes the most rework today?
BOLT-ON is scoped to start narrow on purpose: authorized data, a defined baseline, calibration to your rules, and Shadow Mode running alongside the operation. Your team keeps working the way it works. Expansion happens where the evidence supports it, not on a schedule set by us.
Worth asking: which one to three expensive workflows would you want evaluated first?
Next step
Book a BOLT-ON discovery or a Shadow Mode assessment.
A working session, not a pitch. We look at where the expensive work actually happens in your operation, what data can be evaluated safely, and what LMBR would have to prove before it earns any authority at all.
What you leave with
- One to three named workflows worth measuring, with an owner against each
- An agreed baseline, or a defined method for establishing one
- The data sources required, and the read and write boundaries around them
- A success bar for Shadow Mode that you set, in writing, before we start
No obligation attaches to the session, and nothing is connected to your systems as a result of it.