AI That Gets
Work Done
We learn how your business actually operates, connect the systems you already run on, and build AI infrastructure that performs real work across your organization — around the clock, under your rules.
Engagement
Discover · Design · Build
Train · Maintain · Expand
We don't sell you another AI tool. We build AI into the systems you already run your business on.
Most companies bought AI.
Few of them gained capacity.
The gap is never the model. It is the distance between a capability and the way work actually moves through a business. Big Timber closes that distance by hand.
Where it breaks
- 01
Tools, not capacity
Another subscription arrives. The work it was supposed to absorb stays with your team.
- 02
Advice that stops at the deck
A roadmap is delivered, nobody implements it, and the operation runs exactly as before.
- 03
Automations that don't speak
Nine disconnected scripts, each solving a fragment, none aware of what the others changed.
- 04
No one owns it
An API changes, a workflow silently fails, and the capability quietly decays.
What we do instead
- A
We learn the operation first
Economics, workflows, handoffs, bottlenecks, and the informal work nobody documented.
- B
We connect what you already run
Your ERP, CRM, storefront, marketplaces, finance, and messaging become one environment.
- C
We build and we train
Workflows and agents ship into production, and your people are taught to work with them.
- D
We stay responsible for it
Monitoring, governance, repair, and expansion — the environment keeps compounding.
Your systems stop being
separate software.
Each platform your company runs holds one part of the truth. We wire them into a single operating environment where a change in one is understood everywhere it matters.
Commerce
R1- Shopify / Ecommerce
- Amazon & Marketplaces
- Merchandising
- Pricing
Record
R2- ERP
- CRM
- Accounting / Finance
- Purchasing & Inventory
Signal
R3- Analytics / Warehouse
- Paid Media
- Email & SMS
- Customer Service
Work
R4- Slack / Teams
- Project Management
- Code Repositories
- Internal Knowledge
Integration is not a logo wall. It is permissions, data contracts, error handling, and accountability — the unglamorous infrastructure that makes an AI decision trustworthy enough to act on.
Where capacity
can be built.
Not a claim that AI can do everything. A map of where, in a real ecommerce operation, useful capacity can be added — and where we have built it before.
Know the state of the business without assembling it by hand.
- Daily operating briefing assembled from every system
- Anomaly detection across revenue, margin, and spend
- Plain-language answers over warehouse data
- Board and investor reporting prepared automatically
One business.
Connected intelligence.
Nine isolated automations would each be blind to the others. This is a single system that understands the relationship between them — and knows when a human has to decide.
Isolated automation
Nine tools fire in nine directions. None of them knows what the others just changed.
Connected system
One chain of awareness. Every step below is informed by the step before it.
- 01Marketing
Paid media spend increases
Observed - 02Ecommerce
SKU sales velocity accelerates
Observed - 03Inventory
Coverage falls below supplier lead time
Observed - 04Big Timber
Stockout risk identified
Reasoned - 05Big Timber
Recommended reorder calculated
Reasoned - 06Big Timber
Purchase order prepared
Reasoned - 07Purchasing
Approval request received
Human in the loop - 08Finance
Cash requirement visible
Human in the loop - 09Marketing
Warned about inventory constraint
Human in the loop
Assist. Automate.
Operate.
Most companies stop at the first level. The value compounds at the third — but only where autonomy is deliberately bounded. Not every process should run itself, and we will tell you which ones shouldn't.
Assist
AI helps a person perform work.
Drafting, retrieval, analysis, and summarization inside the tools your team already opens every morning. The human still drives.
Automate
AI performs a defined, repeatable workflow.
A bounded process runs end to end on a trigger or a schedule, with logging, error handling, and a clear owner when it fails.
Operate
AI runs a part of the business, continuously.
The environment monitors the operation, decides what needs to happen, works across systems, executes within defined authority, and escalates exceptions to the right person.
Governance
Autonomy is a setting,
not a promise.
- Defined authority limits per workflow
- Human approval on financial and customer-facing commitments
- Full action logging and audit trail
- Exception routing to a named owner
- Permissions inherited from your existing systems
- Review cadence on output quality
A loop, not
a project.
Each cycle leaves behind working infrastructure and a team that knows how to use it — and reveals the next thing worth building.
- 01→
Discover
Learn the business, its goals, economics, systems, workflows, and real bottlenecks.
- 02→
Design
Prioritize opportunities by value and feasibility, then architect the operating environment.
- 03→
Build
Connect systems and implement the workflows and agents that perform the work.
- 04→
Train
Onboard employees and redesign how the work gets done around the new capability.
- 05→
Maintain
Monitor, troubleshoot, update, support, and govern the environment in production.
- 06↻
Expand
Identify the next opportunity and build the next layer of capability.
Expand returns to Discover — capability compounds with each pass
Managed AI
Operations.
You retain someone to administer your IT. An AI environment needs the same thing: ownership, monitoring, maintenance, permissions, support, and continuous improvement. Without it, capability decays quietly.
Think of it as an outsourced AI department — an operations partner, not a vendor.
Monitor integrations and workflows
Continuous health checks on every connection and process in the environment.
Troubleshoot failures
When something breaks, it is our responsibility to find it and fix it — usually before you notice.
Adapt to change
APIs, models, and software move constantly. We keep the environment current.
Maintain permissions and documentation
Access stays correct, and what was built stays legible to your team.
Support and train employees
New hires onboard, existing staff level up, and questions have somewhere to go.
Review output quality and impact
Regular review of what the system produced and what it was worth.
Identify new opportunities
We are inside the operation, so we see the next constraint early.
Ongoing AI strategy
Where the capability should go next quarter, and what is not worth doing.
Scope expansion projects
New builds specified, estimated, and sequenced against business priority.
Ongoing
M1 — M9
Every month
Find where
AI fits.
We start by understanding the business — not by pitching a predetermined product. One working session, and you will have a clear read on where AI creates real capacity in your operation and where it doesn't.
- How your operation actually runs today
- Where time, margin, and attention are leaking
- Which systems are worth connecting first
- What we would build in the first ninety days