Document Automation, Built on the Stack You Already Run
Every business runs on documents that someone assembles by hand. Contracts, quotes, invoices, certificates, onboarding packs, inbound forms. Staff copy the same data between systems and chase the version that got signed. We build the pipeline that reads those documents, generates them from your data, and files them, on the tools you already run.
The work is not writing the document. It is everything around it.
A pipeline that runs on the stack you already have
What we automate
Six document types account for most of the manual work in a mid-sized operation.
-
Contracts and agreements
Generate agreements from your CRM data with clauses that vary by client, term and jurisdiction. The logic lives in code rather than in nested conditions inside a Word template, so a change is a change in one place.
-
Proposals and quotes
Build a priced proposal from the opportunity record, with the right line items, discounts and terms. Turnaround drops from an afternoon of copy-paste to the time it takes to review the draft.
-
Invoices and finance documents
Generate invoices, statements and remittance documents from the billing record, apply the correct tax treatment, and push them into your accounting system. See our invoice automation build for the full finance pipeline.
-
Certificates and compliance records
Generate certificates, reports and regulatory records with a tamper-evident trail. The system flags an expiry before it lapses instead of after someone notices.
-
Client onboarding packs
Assemble the welcome pack, service agreement, intake forms and account setup documents as one sequence, sent and tracked. See client onboarding automation for the wider flow.
-
Inbound forms and submissions
Capture forms, applications and supplier documents from email, portals and scanned mail. Classify each one, extract the fields, and write them into the right system without rekeying.
How the pipeline works
Five steps turn template-and-spreadsheet work into a connected pipeline. It runs in both directions: it reads inbound files and generates outbound ones.
- 1
Step 1. Capture
Pull files from email, portals, forms and scanned mail. OCR and ICR read printed and handwritten text.
- 2
Step 2. Classify
Sort each file by type so an invoice, a signed contract and an intake form each take the right path.
- 3
Step 3. Extract
Pull the fields that matter: dates, amounts, reference numbers, parties, terms. An AI layer handles the messy prose that rules cannot parse.
- 4
Step 4. Validate
Rules check totals, verify dates, and match records against your system of record. Clean data moves on. Anything odd flags for a person.
- 5
Step 5. Generate, route and file
Produce the outbound document from your templates, route it for review and signature, then file it with the right naming and metadata.
Where AI fits, and where it does not
-
DETERMINISTIC TEMPLATES WIN FOR FIXED OUTPUT
Amounts, dates, legal clauses and reference numbers come from a template driven by your data. A model can approximate; a template cannot. Anything a person would check twice belongs in deterministic code. -
AI READS MESSY INBOUND FILES
Varied layouts, scanned pages and handwriting go through AI extraction. This is the part that used to need a person to read the page, and it is where the hours actually are. -
AI DRAFTS NARRATIVE, A HUMAN REVIEWS
Summaries, cover letters and explanatory sections get an AI first draft that a person signs off. Reviewing a draft takes a fraction of the time writing one does.
Control and compliance you cannot skip
PERSONAL DATA HANDLED WITH CARE
Documents carry personal data, and in healthcare or benefits work they carry health data under HIPAA. We encrypt in transit and at rest and set access rules so that data does not leave the systems meant to hold it.
TAMPER-EVIDENT AUDIT TRAIL
Every document logs its input snapshot, template version, reviewer, signer and timestamp. When someone asks how a document was produced, the answer is one query rather than a forensic exercise.
HUMAN ON THE JUDGMENT CALLS
Approvals, exceptions and anything sent outside the business stay with your team. Full autonomy is not the goal and in regulated work it is not acceptable.
How it worked for Fire Plan Strategies
Facility Services - Fire Safety Compliance How Fire Plan Strategies Eliminated 230 Manual Hours a Month
Lead intake, quotes, invoicing and certificates, automated
- ~230 hrs / monthManual ops time eliminated
- 14 days → 2 daysTime-to-payment
"This is music to my ears. Our accountant is definitely going to love this because she's not going to have to do invoices anymore. The admin staff is also going to love it because they're not going to have to manually do each one of those certificates."
Mariano VelazcoManaging Partner Document automation by industry
The pipeline is the same. The document types, the rules and the regulator are not. These pages cover the version built for each.
-
Insurance
Applications and ACORD forms, policy packets, certificates of insurance, claims files and broker submissions, connected to your agency management and policy admin systems.
-
Legal
Matter documents, engagement letters and client-facing paperwork generated from the practice management system, with the clause logic held outside the template.
-
Finance and accounting
Client reporting, statements and finance documents generated from the ledger, with the review and filing steps attached.
-
Healthcare
Intake forms, records requests and patient-facing documents, handled with the access controls and retention rules the work requires.
The stack we connect to
Component choice depends on your volume and your systems. If a tool has an API, we can connect it.
Both directionsThe same pipeline reads inbound files and generates outbound ones
READ / EXTRACT
GENERATE
E-SIGN
DATA & CORE SYSTEMS
STORAGE / DMS
ORCHESTRATION
AI / NARRATIVE
What a document automation build contains
The production architecture behind every document engagement. See FirePlan Strategies for the pattern regulated document work follows.
The document pipeline
Five components, built once and reused for every document type you add:
Template System
Your templates converted to a generation-friendly format, whether DOCX merge fields, structured layouts or a document library. Brand and layout preserved exactly.
Data Integration
Native connections to every system a document depends on, so merge fields map to the system of record rather than to a spreadsheet someone maintains.
Conditional Logic
Scope, pricing and clauses vary by client, term and jurisdiction. That logic lives in code, which means one change instead of a hunt through nested conditions in the template.
E-sign Routing
Documents route to DocuSign, PandaDoc or SignWell with the right signers and post-signature hooks. Signed copies flow back to storage with the audit trail attached.
Audit Trail
Every generated document logs its input snapshot, template version, reviewer, signer and timestamp into a tamper-evident archive.
Compliance hooks
For regulated work the pipeline integrates with our compliance automation system, so generated documents inherit retention rules, access controls and the audit-trail format your regulator expects.
Storage integration
Generated documents land in SharePoint, Google Drive, Box or your document management system with the right foldering, naming and metadata, so nobody has to ask where the signed copy went.
How we engage
Every engagement starts with a workshop that maps your document inventory: which documents, how many per month, which data sources feed them, and who approves them. Then we build, one document category at a time.
If we cannot show ROI inside six months, we do not take the project.
Automation Discovery Week
Builds
Ongoing
Document automation FAQs
The questions we get from operations and compliance leaders evaluating a build.
What is document automation?
Document automation is the use of software to generate documents from data you already hold, and to read the documents that arrive from outside, without a person retyping anything. In practice it covers both directions: producing contracts, quotes, invoices and certificates from your systems, and extracting the fields from inbound forms and files so they land in the right place.
How is document automation different from document management?
A document management system stores and organises files that already exist. Document automation produces them and processes them. The two work together: our pipelines file their output into whatever DMS you run, with the naming and metadata already applied.
Do you replace the systems we already use?
No. We connect them. We read from and write to your CRM, finance tools, storage and any industry-specific system, through their APIs. If a tool has an API, we can wire it in.
Should the documents be generated by AI or from templates?
Templates, for anything with a fixed correct answer. Amounts, dates, clauses and reference numbers come from your data through a template, because a model can approximate and a template cannot. AI earns its place reading messy inbound files and drafting narrative sections a person then reviews.
Can it read files that arrive in a different format every time?
Yes. AI extraction reads varied layouts without a fixed template per sender, and OCR and ICR handle printed and handwritten text. This is normally the part of the work that was consuming the most hours.
How does this handle personal data and compliance?
We encrypt data in transit and at rest, set access rules so information stays inside the systems meant to hold it, keep a time-stamped audit trail on every action, and apply your retention rules. Where health data is in scope, it is handled under HIPAA.
How long until the first results?
The first document category goes live in weeks rather than months, and each category pays for itself before the next one starts.
See where document automation would pay back first
The Automation Discovery Week maps your document workload and tells you which category would pay back first. Run the numbers with our ROI calculator, then talk to us. See the FirePlan Strategies case for the pattern regulated document work follows.