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Local models

Articles grouped by business problem, industry, and system type.

How to evaluate an LLM before deployment

Test a private LLM on business documents: quality, abstention, access, latency and error costs. How Syntalith defines deployment acceptance criteria.

local-modelsllmprivate-aifine-tuning

Local LLM on your computer: where to start

Want AI on your own computer? Learn how to choose a model, memory and tools. Syntalith helps individuals and businesses, including hardware advice.

local-modelsllmprivate-aifine-tuning

Local LLM or OpenAI, Claude and Gemini?

When should you self-host a model or use OpenAI, Claude or Gemini? Compare quality, privacy, operating work and costs for a business deployment.

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What does a private LLM really cost?

Compare API and private LLM costs including hardware, hosting, maintenance and corrections. A worked scenario and inputs for a Syntalith assessment.

local-modelsllmprivate-aifine-tuning

Taking work history out of a private AI application

A company wants to change its private AI application, but employees have conversations they return to for later tasks. A file containing answer text may not be enough: they also need the questions, documents and an indication of which result was used. Assess portability before choosing a tool and before closing the existing service.

local AIAI deployment

Local AI captions for internal company videos

A team wants captions for internal videos, but the material cannot go to just any online service. A local speech recognition model can prepare draft text. Publishing the video still requires correction, readable segmentation and alignment with playback.

local AIAI deployment

Local AI for reviewing clinic administrative questions

A clinic operations manager wants to know which appointment information needs a clearer explanation. Message totals alone reveal little: a general booking category may contain questions about confirmation, updating details or whom to contact. A local AI application can help group the contents of a prepared set of administrative messages and show what is worth discussing with the front desk team.

local AIhealthcare administrationmessage analysis

Local AI for document batches

Not every local AI task needs an answer during a conversation. A team may need descriptions the next morning for documents received the day before. In that situation, consider an application that accepts an agreed batch and returns work for review, without requiring an employee to submit each file separately.

local AIAI deployment

Local AI table extraction: the review work that remains

Moving a table from a document into a spreadsheet is useful only when values stay with the correct rows and headings. A company considering a local model needs to compare extraction and correction with its current tool. A quickly produced spreadsheet may still require lengthy source checking.

local AIAI deployment

Private AI across group companies: shared service or separate environments

A group wants private AI for several companies. Shared infrastructure may be a starting point, but teams have different data owners and application needs. Before combining them in one service, establish which decisions belong to the group and which each company needs to make independently.

local AIAI deployment

Local AI for preparing a text copy to share externally

An employee wants to share a case description with a partner, but the original contains information the recipient does not need. Preparing a copy manually requires careful reading while preserving the document's meaning. A local application can suggest passages to remove or replace, with an employee approving the revised version before sharing it.

local AIAI deployment

Local AI search for company presentation slides

An employee remembers a slide comparing options but cannot recall the presentation's name. They search folders and open files when all they need is material for a new discussion. Local slide search can help turn a description of the content into a specific page and its source.

local AIAI deployment

Who will maintain local AI when IT is already stretched?

A company wants AI in its own environment, but its IT team already handles computers, access and business systems. Nobody has capacity to take on the model service as well. Before buying, establish what an outside provider would manage, which decisions stay with the company and whether data requirements actually justify an installation on your premises.

local AIapplication maintenanceIT management

Local document search across languages

An employee asks a question in Polish, but the needed information is in an English report. Matching the same words may not find it, while translating the entire archive would be a separate undertaking. Local multilingual search can help reach a source through its meaning while keeping the original available to read.

local AIAI deployment

A downloadable model: what to review before deployment

The technical team has found a model it can download and run. Before commissioning an application, the company still needs to establish whether its terms fit the intended product and users. File access and permission for a particular use are separate questions worth resolving before expanding the solution.

local AIAI deployment

Private AI for reviewing an email archive

A team returns to a completed project to find how earlier decisions developed. It has an email export, but searching by subject returns replies and repeated quotations of the same message. A private AI application can help select passages to read and connect them to original emails in the archive.

local AIAI deployment

Private image search using content descriptions

A team has a photo archive, but filenames do not help locate a particular shot. An employee remembers a place or object's appearance and browses folder after folder. Private image search by description can bring them to candidates they can inspect before use.

local AIAI deployment