AI for
professional services.
Consulting, engineering, design, and agency businesses. The product is knowledge and delivery capacity — and both are constrained by how much of the firm's own work it can find and reuse.
The firm's knowledge should not disappear into the last project.
Prior work, proposals, research, and project history accumulate faster than anyone can organize them, and the cost shows up as rework, slow proposals, and uneven delivery.
Knowledge is trapped in projects
The best version of the answer is inside a deliverable from two years ago that nobody can locate.
Proposals take senior time
The people best placed to win work are the people whose hours are already sold.
Capacity is a guess
Committing to a start date without real workload visibility is how delivery quality slips.
Meetings do not become actions
Decisions are made verbally and reconstructed later from partial notes.
Reporting is manual
Project status, utilization, and margin are assembled by hand for every review.
Billing lags the work
Time capture and invoice preparation are consistently the last thing anyone does.
The work worth
building around.
Not a menu to buy from. These are the places where connected systems most often remove work, improve a decision, or keep the operation moving.
- 01
CRM & Opportunity Intelligence
Pipeline context, relationship history, and next steps surfaced without anyone maintaining it manually.
- 02
Proposal & SOW Preparation
Drafts assembled from relevant prior work, scope patterns, and rate structures — priced by a person.
- 03
Research
Background, market, and technical research synthesized with sources kept attached.
- 04
Project Intake
New engagements set up consistently: workspace, structure, materials, and owners.
- 05
Meeting-to-Task
Conversations turned into decisions, owners, and tasks in the systems the team already uses.
- 06
Knowledge Management
The firm's own work made retrievable and kept from going stale.
- 07
Document Retrieval
Contracts, specs, and deliverables searchable across drives, email, and project tools.
- 08
Project Reporting
Status, risk, and progress assembled from real project data on a cadence.
- 09
Workload Visibility
Capacity and commitments reviewed together before a date is promised.
- 10
Time & Billing Support
Time capture prompts, draft invoices, and exception flagging ahead of the billing cycle.
- 11
Client Communications
Updates and follow-ups prepared from actual project state, sent by the account owner.
- 12
Training & Onboarding
New staff brought up on how this firm works, from the firm's own material.
- 13
Management Reporting
Utilization, pipeline, and margin visible without a monthly assembly exercise.
An opportunity advances. The firm's memory shows up with it.
Prior work is retrieved, a draft is prepared, and capacity is checked — before anyone commits to scope, price, or a start date.
- 01Sales
Opportunity advances to proposal stage
Observed - 02CRM
Relationship, history, and prior conversations retrieved
Reasoned - 03Knowledge
Relevant prior work and comparable engagements surfaced
Reasoned - 04AI Environment
Proposal and SOW draft assembled with sources attached
Reasoned - 05Delivery
Capacity and staffing checked against the proposed timeline
Reasoned - 06Partner
Scope, price, and commercial terms approved
Human authority - 07Operations
Project workspace and structure created on acceptance
Reasoned - 08AI Environment
Kickoff tasks, materials, and owners generated
Reasoned - 09Client Lead
Kickoff communication reviewed and sent
Human authority
One illustrative workflow, not a product. The architecture behind it — how systems, context, and approvals fit together.
What stays
with a person.
The environment prepares and retrieves. Professional judgment, scope, and what the firm puts its name to remain with the people qualified to give it. Where work touches licensed legal, accounting, or medical judgment, that judgment stays with the licensed professional.
- Scope, pricing, and contractual commitments
- Professional advice and any licensed judgment
- Staffing decisions and delivery commitments
- What is sent to a client under the firm's name
- Handling of confidential client material and access to it
How Big Timber works
We don't start with
a product.
We learn how the business works, then identify where connected AI creates useful capacity — and where it does not.
See the engagement model →Discover
We learn how the operation actually runs — systems, handoffs, and where work stalls.
Design
We map where connected AI creates capacity, and what stays with a person.
Build
Integrations, context, workflows, approvals, and logging built into your environment.
Train & Maintain
The team is brought with it, and the environment keeps an owner afterwards.
Find where AI fits in yours.
A working session across pipeline, proposals, knowledge, and delivery. We will identify where connected AI recovers senior time — and where it would only add noise.