B:Side Advisors
Use case / Document automation

First drafts of contracts, estimates, proposals, and invoices in 90 seconds.

Small firms lose hours to document work a senior person should not be doing. AI document automation reads the source data (matter, job, order, quote), assembles the right template, and drafts the whole thing in your voice. Your senior reviews, edits, and sends. Every document improves because every human edit tunes the next draft.

Christopher Myers2026 / Workflow guide
Scene / 01
A 16-person professional services firm

It is 4:55 on a Thursday. A senior partner has a 90-minute window before she has to leave for a client dinner. On her list: draft an engagement letter for a referral that came in Tuesday, review a fee estimate for a new matter, and update a template proposal for a long-term client renewal. Three documents. Each is 30 to 45 minutes of focused writing. She has 90 minutes total.

She will do two. One will wait until Saturday morning, when she is less sharp. The referral will sit another day. Referrals do not wait. This happens every week. Nobody counts the cost because it does not show up as a line item.

This is where AI document work lives or dies. Not in a generic word processor. In the 4:55 p.m. Thursday window.

Document work is the highest-leverage time that gets the least attention.

The senior partner who bills at $450 an hour will not spend a Saturday mapping document templates. But they also will not skip writing the engagement letter. So the work happens at night.

Professional services benchmarks consistently show 20 to 35% of a senior's week spent on document work: engagement letters, fee estimates, scope memos, deliverables, proposals, reports, client summaries. The template exists in their head. The source data exists in the matter/job file. The assembly work is a rote transfer that takes a human 30 to 60 minutes per document.

The second cost is that document delays slow down the business. A proposal that takes a week costs you the deal. An engagement letter sitting unwritten means the matter does not formally open. An estimate delayed is a job lost to whoever sent one first. Speed of document output is speed of revenue.

The third cost is that senior work has to be senior. When a partner writes the same engagement-letter paragraph for the 40th time, the work is not senior. It is transcription. AI that drafts that paragraph in your voice frees the partner for the work only they can do.

Sources referenced
  • Clio Legal Trends Report Non-billable administrative and document-related time across small law firms.
  • AICPA PCPS MAP Survey Realization rate and administrative overhead benchmarks for accounting practices.
  • Deloitte Insight to Action, automation in professional services ROI benchmarks for document-automation deployments in mid-market firms.

How document automation actually works.

Five steps. Anchored in your actual templates and actual past documents. Not generic generation.

Workflow 01

Step 01. Codify the 4 to 6 document types that matter most.

What we'd build

We sit with your senior operators for a week and capture your real templates. Not the template file nobody uses. The actual document pattern that ends up getting sent. We version-control it. Changes to the template flow through to the draft system.

Vendors we'd evaluate
  • Gavel (Documate)
  • Lawyaw
  • Harvey
  • Spellbook

Vendor-neutral. No reseller margins.

Workflow 02

Step 02. Pull source data from your system of record.

What we'd build

Each document has inputs. An engagement letter needs matter details, fee structure, client info. An estimate needs job specs, parts, labor. A proposal needs scope, deliverables, timeline. We wire the draft engine to pull from your CRM, practice management, or project system. Not from a spreadsheet someone keeps updating.

Vendors we'd evaluate
  • Clio
  • Karbon
  • Ignition
  • ServiceTitan
  • HubSpot
  • Salesforce

Vendor-neutral. No reseller margins.

Workflow 03

Step 03. Draft in your voice.

What we'd build

The model is tuned on your past 200 signed documents. It writes the way your firm writes. Senior stylistic tics, preferred phrasings, regional conventions. Where it is unsure, it flags a placeholder for human judgment instead of making up content.

Vendors we'd evaluate
  • OpenAI API
  • Anthropic API
  • Gavel
  • Spellbook

Vendor-neutral. No reseller margins.

Workflow 04

Step 04. Track every human edit to improve the next draft.

What we'd build

Senior edits a draft. The edits are captured. Next draft of the same document type incorporates the edit patterns. Over six months the drafts converge on what your senior actually signs. Less editing every cycle, without anyone training the model explicitly.

Vendors we'd evaluate
  • Azure OpenAI
  • Custom prompt management
  • LangSmith

Vendor-neutral. No reseller margins.

Workflow 05

Step 05. Preserve the review trail for compliance.

What we'd build

Every draft is logged. Every human edit is logged. Every sent version is versioned. If a regulator or auditor asks what was sent and who approved it, you can answer in under 60 seconds. This matters for regulated industries and it is a non-negotiable for us.

Vendors we'd evaluate
  • NetDocuments
  • iManage
  • Box
  • SharePoint + audit logs

Vendor-neutral. No reseller margins.

Why small firms win at document automation.

BigLaw spent $500M on Harvey in 2024. You can ship a better-fitting automation for your firm in 6 weeks for less than a week of their partner time.

Enterprise document automation is politics. Fifteen partners argue about which template is canonical. The compliance team vetoes everything. Procurement stretches the project to a year. A small firm has one managing partner, a shared Google Drive, and the willingness to decide.

Second, your document set is tractable. A small law firm has maybe 20 recurring document types. A small accounting firm has 10. A trades shop has 6. Automating the top 5 captures 80% of the time cost. That is a 6-week sprint, not a 14-month program.

Third, the voice fit is cleaner. Your voice is one person or a small partnership. The model can learn your specific style in two weeks. The enterprise version is trying to average across 300 partners and lands somewhere bland.

Mid-post · 30-minute scoping call

Want a 30-minute scoping call for your document load?

Bring the top three documents eating your seniors' time. We will tell you honestly which of them are good automation candidates, which are not, and what a first sprint actually costs and delivers.

Three things document AI will not fix.

These are the conversations worth having before we quote a sprint.

01

If your templates are incoherent.

Every senior uses their own version. No two engagement letters look alike. The first phase is codifying, not automating. This is valuable work, but it is the sprint before the sprint. We will name it if we see it.

02

If the bottleneck is decisions, not writing.

If a proposal takes a week because three partners have to approve it, AI drafting does not help. The bottleneck is the review cycle. That is a process problem, not a drafting one.

03

If the document is genuinely bespoke.

The one-off M&A agreement, the novel patent claim, the bespoke architecture brief. These are not where AI drafts live. AI earns its keep on the 80% of documents that are variations on a pattern. The bespoke 20% still takes a senior.

How we'd work with you on document work.

Readiness Audit inventories your document types, measures senior time spent per type, and ranks them for automation readiness (pattern recurrence, data source cleanliness, review complexity). You walk out with a readiness score and a ranked list.

The first sprint usually targets 3 to 5 document types in the top half of the ranking. Written acceptance tests specify the time-save target (e.g. 'a standard engagement letter drafts in under 2 minutes and requires under 15 minutes of senior edit in 85% of cases'). Weekly demos. Fixed price band.

Managed handles template evolution (new practice areas, new regulations, new firm voice), adds new document types at 1 to 3 per quarter, and measures edit-time drift. Month-to-month, 30-day exit.

Questions firms ask about document AI.

The questions operators in this vertical actually ask on the first call.

01How do you handle privilege and confidentiality?
Document data stays in your existing systems. Models are called via vendor APIs under data-processing agreements that prohibit training on your data. For regulated industries we often deploy via Azure OpenAI or Anthropic's private deployment to keep everything inside your tenant.
02What about malpractice risk?
Every draft is clearly marked as a draft. A senior reviews and signs every document. The AI never autonomously sends. We document this in the engagement so your insurance carrier has a clean audit trail.
03Will it handle jurisdiction-specific clauses?
Yes, if we encode them. Different states have different rules, different bars have different ethics guidance, different industries have different defaults. These become structured inputs the draft engine respects.
04What happens when a regulation changes?
Template updates ripple to future drafts automatically. The Managed retainer watches for relevant regulatory changes in your practice area and updates affected templates. You get a report of what changed and when.
05Can we keep using Word?
Yes. Drafts export to Word. Track changes preserve human edits. Nothing about this forces a tool switch. For firms on iManage, NetDocuments, or Clio, we integrate so the draft lands where the firm already works.
06What if the firm rejects a draft?
Every rejection is captured. If the assistant is generating content the senior does not trust, we tune it in the next iteration. Most firms see rejection rate drop from 30% at launch to under 10% by the end of quarter one.
End of post · Next step

Your partners are writing at night. Get the nights back.

Thirty minutes, a scoping call. We will ask about the three documents eating the most senior time and tell you which of them are right for a first sprint.

What the 30 minutes delivers
  • 01A short list of AI opportunities specific to your shop.
  • 02A rough ROI range and a sense of which to build first.
  • 03An honest answer: audit now, wait a quarter, or skip us.
Free · 30 minutes · No deck