Find every place a local model can run your daily work
We map your operations, compare local models with OpenAI and Anthropic, and show where on-prem AI cuts cost without sending company data to a vendor.
Ækora
Operations lead
Local models change the cost of everyday AI.
data stays inside your network
cost after hardware, not per token
local for volume, cloud only for exceptions
Most teams send routine work to OpenAI or Anthropic because it is easy to start — not because every task needs a frontier API.
Local models win on high-volume, repeatable work: documents, triage, drafts, search, and internal Q&A where the pattern is stable.
We keep a cloud model in reserve for rare, high-stakes exceptions so you do not overbuild hardware or overpay for every page.
Cloud APIs versus local models
OpenAI and Anthropic are not the wrong tools. They are the expensive default.
OpenAI / Anthropic
Per token or per page. The bill grows with every invoice, email, and draft.
Local models
Hardware plus electricity. Unit cost falls as volume rises.
OpenAI / Anthropic
Prompts and files leave your network for OpenAI, Anthropic, or similar APIs.
Local models
Documents, tickets, and knowledge stay on servers you control.
OpenAI / Anthropic
Rare, hard, or brand-new tasks where a frontier model still wins.
Local models
Repeatable daily work: extraction, triage, search, drafts, and internal answers.
OpenAI / Anthropic
Fast to start, expensive to scale across a whole department.
Local models
A workstation or small GPU cluster often pays back once volume is steady.
Use cases we look for first
Document intake
Invoices, forms, contracts, and receipts extracted on your hardware instead of a metered vision API.
Inbox and ticket triage
Route support, AP, and HR mail by intent so people only touch the items that need a decision.
Internal knowledge search
Answer policy, product, and process questions from your own files without sending them to a vendor.
Drafts that stay internal
First-pass replies, meeting notes, and report summaries written next to the source systems.
Contract and policy review
Flag dates, obligations, and unusual clauses before legal or finance spend time on the pack.
Exception routing
Keep a cloud model for the hard 5% while the other 95% runs locally at a fixed cost.
An opportunity map, then a pilot that pays for itself.
You leave with a ranked list of workflows, a cost comparison against your current API spend, and a recommended local stack — not a slide deck of generic AI ideas.
Map the week
We sit with operations, finance, and support to list the work that repeats: documents, inboxes, search, drafts, and reviews.
Score local versus cloud
Each workflow gets a simple score: volume, sensitivity, accuracy bar, and whether OpenAI or Anthropic is still worth the premium.
Pilot the first win
We stand up one local model on a real workload — usually document processing or triage — and measure cost, quality, and handoff.
From the blog
Further reading
- 27 August 2026 · Consulting workflowsThe hybrid AI stack: local models for 95% of your documents, frontier APIs for the exceptionsHow a hybrid AI stack pairs local models with frontier APIs: the 95/5 split, €660 vs €1,100–1,800 a month at 100,000 pages, and rules for the 5% that leaves.Read the article
- 20 August 2026 · Consulting workflowsWhich workflows should run on local models? A four-axis scoring method for on-prem vs cloud AIA scoring method for which workflows should run on a local LLM and when to use on-prem vs cloud AI: volume, sensitivity, stability and availability, 0–3 each.Read the article
- 11 August 2026 · Consulting workflowsStop paying OpenAI per invoice: a workflow-first method to reduce API costsHow to reduce OpenAI API costs without a model swap: inventory recurring workflows, measure tokens per unit, and route each to a local, mini or frontier model.Read the article
Ready to see where local AI belongs?
We will walk your daily operations, compare them with OpenAI and Anthropic, and point to the first local-model win.
Book a discovery call