Customer data in ChatGPT and Claude: prepare the document first
Which details does the model need? A complaint example, the difference between anonymisation and pseudonymisation, and the cost of implementation support.
Syntalith blog
Start with the problem you need to solve. Explore team training, agents, automation, internal knowledge, custom models and alternatives to costly software.
Shadow AI: bring ChatGPT and Claude use into a company rollout
Staff already use AI, but the company cannot identify the accounts, files or connections. Review existing work and move useful tasks into an approved environment.
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.
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Fine-tuning, RAG or training your own model?
Choose RAG, LoRA fine-tuning or a small custom model for a business task. Understand training data, evaluation and adaptation costs with Syntalith.
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Jev 1.13 for business classification and routing
Where should you test Jev and small decision models? Explore ticket routing, document completeness, confidence thresholds and a Syntalith-led pilot.
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Local Jev 1.13 alternatives: Kev and TinyJev
Can Jev run locally? Explore Kev, TinyJev and other approaches to private decision models, with selection, fine-tuning and deployment from Syntalith.
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TypeSafe Jev 1.13: a model for application decisions
Jev 1.13 on OpenRouter: typed decisions, probabilities, pricing and 32k context. Learn how Syntalith can evaluate the model for your business.
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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.
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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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Qwen, DeepSeek, Kimi and GLM: what to self-host?
Compare Qwen3.8, DeepSeek V4.1, Kimi K3 and GLM-5.3. Understand weights, hardware needs and model selection for private deployment with Syntalith.
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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.
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Private LLMs: data, EU hosting and on-premise
Where should an LLM process company data? Compare on-premise servers, EU hosting and network isolation, including access, logs and GDPR review.
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A SaaS price increase: negotiate, switch or build
Your SaaS provider has sent a higher renewal quote, and someone has suggested building an application instead. Before that becomes a project, establish what the company would be paying for and when it could realistically stop using the current product. The renewal deadline may require a different decision from the eventual choice of system.
custom software
AI for an operational branch opening review
Before a branch opens, individual teams are prepared for their tasks, but a joint rehearsal shows that pickup and return customers will use the same desk. The branch manager needs to agree on an arrangement with headquarters and employees. An AI agent can gather rehearsal observations and participants’ proposals so that discussion starts with the actual problem.
AI for reviewing a partner’s support needs
A channel partner says the product is too difficult to use. The account manager has a case report, but the number of tickets does not establish what to offer: training, a support discussion, or a product request. An AI agent can prepare a review of the descriptions and outcomes so the meeting addresses the partner’s actual difficulties.
AI for custom parts quote preparation
A customer sends a part drawing and asks for a quote. The estimator opens the attachment, then asks sales about the production quantity. The customer’s answer sits in another thread and still does not explain the first order. An AI agent can help assemble the quote material and gather the explanations specialists need.
AI for fleet repair coordination
A repair shop expects to finish the work, and dispatch asks whether the vehicle can go back on the schedule. The fleet coordinator checks the latest email, calls the shop, and arranges collection. An AI agent can gather those records around the vehicle and prepare the question needed for a useful update to dispatch.
AI for preparing a plant shift handover
The incoming shift supervisor reads the log, then calls the person who just left: who picked this up, and what are we still waiting for? The answer may be in a warehouse message that never made it into the log. An AI agent can help prepare a handover with open issues and the latest replies before the supervisors talk.
AI for coordinating product recall replies
After a product recall is authorized, the coordinator collects distributor responses. One describes stock found in a warehouse, another reports a return, and a third only acknowledges the message. An AI agent can help interpret those replies and identify conversations that still need follow-up within the campaign scope set by the company.
AI agents for sales-to-delivery handoffs
A project manager takes over a sold service and prepares for the first customer meeting. The CRM contains a short description, while the details needed for delivery sit in the proposal and the salesperson's conversations. An AI agent can bring together the sold scope and questions to resolve before work begins. The manager gets a starting point for discussing the assignment with sales.