Professional services · Local & private AI

Local and private AI for professional services

Professional services firms hold documents they are professionally obliged to protect. That obligation is the reason a lot of firms have quietly banned the tools their people would otherwise use. Self-hosting is the version of this that survives a conflicts check.

05Self-hosted inference · Retrieval on private data
Local & private AI05
Self-hosted inferenceRetrieval on private dataDe-identification
Professional servicesIllustrative

Local & private AI models

Self-hosted inference, fine-tuning, retrieval on private data, and de-identification.

Local & private AI · Professional servicesOne pairing of the matrix
Covers
Agencies · Advisory & firms · B2B services
Architecture
Unchanged from every other vertical — only the breaks differ
Engagement
A defined build, or run under management

What usually breaks

Before anything gets built.

The same failures recur across professional services. Strygon maps the specific system before proposing anything, but these are the ones worth checking for.

Manual follow-up

Follow-up depends on a person remembering, so warm leads cool while everyone is heads-down on delivery.

Tool sprawl

Five tools that don’t talk, each holding a piece of the truth, none of them the whole picture.

Onboarding drag

Every new client kicks off a manual checklist that eats a day of senior time that should bill.

Recurring in professional servicesObserved pattern · the specific system still gets mapped

The approach

What Strygon does about it.

Local & private AI models, aimed at those failures specifically rather than at a generic checklist.

01Local & private AI
Review that stays inside the firmLocal & private AI
01
Part of the scoped build

Review that stays inside the firm

Document review and summarization running on infrastructure the firm controls.

02Local & private AI
Drafting grounded in the firm’s own workLocal & private AI
02
Part of the scoped build

Drafting grounded in the firm’s own work

Retrieval across precedent and prior matters, citing internal sources rather than inventing them.

03Local & private AI
Defensible by constructionLocal & private AI
03
Part of the scoped build

Defensible by construction

There is no third-party processor to disclose, because there is no third party.

The approach for this pairingScoped in writing before work starts

What gets built

Concrete deliverables.

Everything in local & private ai models, applied to how professional services actually runs.

Self-hosted / on-prem LLM and vision deployment
Fine-tuning, evaluation, and quantization pipelines
Retrieval (RAG) over private data
On-device and edge inference
De-identification and policy guardrails
In scopeScoped in writing before work starts

Also for this industry

Other parts of the same system.

Start

Start with what’s broken.

Send the situation in a paragraph. Strygon comes back with a read on what’s likely wrong and what it would take to fix, before anyone talks about price.

Most builds start withleads dying in an inbox., three half-finished pipelines., follow-up nobody owns., numbers that never agree., four vendors blaming each other.

What to send
A paragraph. What broke, and where it shows up.
What comes back
A read on what is likely wrong and what fixing it takes.
Price
The last conversation, not the first