Advisory

Document AI consulting: architecture, build-versus-buy, and accuracy strategy

Independent advisory for teams making expensive, hard-to-reverse decisions about document AI: which architecture, which models, build or buy, what it will really cost at volume, and how to know whether it is working. I am an engineer who ships these systems, not a reseller — I have no vendor relationships to protect.

No vendor commissions, reseller margins, or partner incentives
Recommendations grounded in measurements on your documents
Written deliverables your team and your board can act on
Available as a fixed-scope review or an ongoing fractional role

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What advisory work looks like

Three situations it fits. A team has built a document AI feature that works in the demo and not in production, and needs to know whether to fix it or restart. A team is about to commit to a vendor or an architecture and wants an independent read before signing. Or an investor needs technical diligence on a company whose core claim is extraction accuracy.

In all three the valuable output is the same: a clear, written, measured answer that someone can act on. Not a slide deck of industry trends.

I work as an engineer throughout. If a question can be settled by running your documents through three pipelines and scoring the results, I will run them rather than reason about it.

Advisory areas

Architecture review

Your current or planned document AI architecture assessed for accuracy ceiling, failure modes, cost at projected volume, and operational risk — with specific, prioritised changes rather than general principles.

Build versus buy

An honest comparison of commercial IDP vendors, hosted model APIs, and a custom build for your specific corpus, including the total cost of ownership that vendor pricing pages leave out.

Model and vendor selection

Candidate models and vendors scored on your documents against ground truth. Public benchmarks rarely predict performance on a specific corpus; this replaces that guesswork with measurement.

Accuracy strategy

Defining what accuracy means for your use case, building the ground-truth set, choosing the metrics that reflect business impact, and setting the confidence thresholds that govern human review.

Cost and unit economics

Per-document cost modelling across extraction methods and providers, with the routing strategy that keeps the expensive path rare. This frequently pays for the engagement several times over.

Technical due diligence

For investors and acquirers: independent assessment of whether an AI extraction company's accuracy claims survive contact with a ground-truth benchmark, and how defensible the underlying engineering actually is.

How to engage

Advisory call

$180 / hour

Same or next week

A focused working session on a specific decision, with written notes afterwards.

60–90 minutes, screen-shared and working
Reviewed materials in advance
Written summary and recommendations
No minimum commitment

Written review

from $1,400

1–2 weeks

A fixed-scope assessment with a document your team can build against and your leadership can read.

Architecture, vendor, or diligence review
Measured comparison on your documents where relevant
Prioritised recommendations with effort estimates
Cost model at your projected volume
Follow-up session to work through it

Fractional AI engineer

from $1,800 / month

Rolling, 2-month minimum

Ongoing technical leadership for teams building document AI without a senior specialist in house.

Regular working sessions with your engineers
Design review on extraction and retrieval work
Hands-on contribution where it unblocks fastest
Hiring support for AI engineering roles

Questions this work answers

Should we build this ourselves or buy an IDP vendor?
Our extraction is 85% accurate and the business needs 98% — is that reachable?
Our LLM bill is growing faster than revenue. Where is the waste?
Is our RAG system underperforming because of retrieval or generation?
Can we run this on our own hardware for compliance reasons?
This vendor claims 99% accuracy. How do we verify that?
We are acquiring a document AI company. Is the technology real?

Frequently asked questions

Do you take commissions from vendors you recommend?

No. I have no reseller agreements, referral fees, or partner commissions with any AI provider. That independence is the point of hiring an engineer rather than a systems integrator.

Can you review work done by another vendor or agency?

Yes. The review is on the engineering and the measured results, not on the people. Where the existing work is sound I will say so — I would rather hand back a short report saying the build is fine than manufacture a problem.

Do you sign NDAs?

Yes, as a matter of course, before any materials are shared. For diligence engagements I will also confirm I have no conflicting engagement with the target or a direct competitor.

What do you need from us to start?

A representative document sample, a description of the current or planned architecture, and a clear statement of the decision you are trying to make. If a ground-truth comparison is part of the scope, expected outputs for a subset of documents as well.

Can an advisory engagement turn into a build?

Often it does, but the advisory deliverable is written to stand alone and to be executable by your own team or another vendor. Recommending work for myself is exactly the bias that makes most consulting worthless.

Bring me the decision, not the project

Tell me what you are choosing between and what evidence you have so far. If an hour will settle it, I will say so rather than propose an engagement.

Document parsing & extraction