Local AI development
Assistants and analysis tools that run on your devices, sized to your hardware, your task and the information you want to keep close.
- Offline assistants
- Document search
- On device vision
- Desktop apps
Our point of view
Algorithmic Network builds custom AI-powered solutions, using custom models or fine-tuning where your project needs them. We keep sensitive information on your devices or inside infrastructure you control wherever we can, and when a hosted model is the better tool, we connect it carefully. Your team gets the benefits of AI without needless exposure.
We design around clear data boundaries and limited collection. Your privacy requirements decide where information is processed and how the system is run.
We explain capabilities, data flows and limitations in plain language, so the people using a system understand what it does and why.
Clear permissions, useful feedback and human review for the actions that matter. People stay in charge of their information and their decisions.
Deployment
We choose the deployment around your information, your hardware and your rules. Private options come first, and trusted hosted AI joins in when it is the better fit for quality, scale or cost.
Local first, never local only. Many projects combine both: private models for sensitive work and hosted models where they add real value.
Services
Two ways to work with us. We advise when you need clarity, and we build when you need software that works on day one, locally, privately or in the cloud.
Assistants and analysis tools that run on your devices, sized to your hardware, your task and the information you want to keep close.
AI inside controlled environments, with deliberate choices about data access, deployment and who operates it.
Knowledge search, document assistance and focused automation that fit the way your team already works, with references and human review for important actions.
Custom model development, fine-tuning and complete AI products, from dataset preparation and evaluation to deployment.
When local is not enough, we integrate hosted models with minimal data sharing, clear provider terms and the same review steps.
Products
We build and run products on the principles we bring to client work. Private by default, useful every day, and designed for the people who rely on them.
Product family
A family of products for commerce. Run the shop floor, sell online, protect your data and create with AI, all from one connected suite.
Products, inventory, orders and daily retail operations, with local tools and optional connected services.
Explore Retailist AppA focused online store connected to the catalog and operations you manage in Retailist App.
Explore Retailist Store
Encrypted backups, version history and recovery for supported commerce data, with clear storage and access boundaries.
Explore Retailist Cloud
AI tools for product imagery, scenes and content across catalogs, storefronts and campaigns.
Explore RetailistAIPrivate link shortener
Short, secure links with end to end encryption and analytics that respect your visitors. No ads and no trackers.
Visit FynlinkPrivate AI resume analysis in your browser
Free and open source. Compare your resume with a job description privately in your browser, powered by our custom models.
Visit Local ATS (opens in a new tab)We partner with founders and teams to build private, AI native products, from the first prototype to launch.
Let’s talkHow we work
We turn a clear use case into a useful AI system through discovery, evaluation, development and ongoing review. Every step ends with something you can see and judge.
Understand the task, the people and the information involved. Agree on the outcome and the privacy requirements.
Compare deployment options and test the riskiest assumptions with a focused prototype on your real tasks.
Build the application and, where useful, develop or fine-tune its model, with quality checks and review for important actions.
Prepare deployment and handover, then review quality, security and operating cost as the system grows.
Most projects start with a short call and a focused discovery.
Questions
The things teams usually ask before starting with private AI. Something else on your mind?
Ask us directlyLocal AI runs models on hardware you control, such as a laptop, a workstation or your own servers. Prompts, documents and results stay with you instead of being sent to an outside service.
No. We start with local and private options, and we use hosted AI services when they are the better fit for quality, scale or cost. In those cases we limit what is shared, mask sensitive details where possible and choose providers with clear data terms.
For many focused tasks, yes. Search over your documents, drafting, classification and extraction often work very well with open models. We test on your real tasks before recommending anything, and we say plainly when a larger hosted model is the better choice.
Often less than you expect. Many assistants run well on a modern laptop or a single workstation. We size the model to your hardware and your task, and recommend upgrades only when they clearly pay off.
Yes. We develop custom models and fine-tune existing ones for focused tasks. We start with your data quality, permissions and a baseline, then evaluate results on separate test examples before deployment.
Only when you authorise it for custom model development or fine-tuning. We agree on the dataset, permissions and training environment first. Your information is not used to train shared models or for unrelated projects.
Yes. We connect to the tools and data sources you already use, and we design workflows around how your team works today rather than asking it to change everything at once.
With a short call about your goals. If there is a good fit, we agree on a focused discovery and a prototype before any larger build, so you can judge real results before committing further.
Ready to start a project or just want to chat? We'd love to hear from you. Select a contact method below that best suits your needs.
The fastest way to get a detailed response. Choose a time that works for you.
30 min • Models, fine-tuning and deployment
45 min • Workflow and model review
60 min • Scope, approach and next steps
By scheduling a meeting, you agree to our privacy policy. We respect your privacy and will only use your information to schedule and conduct the meeting.
For general inquiries, feel free to reach out directly.
Usually within 48 hours