A personal AI on hardware I control
Explore Kvantia AI's working prototype and early-access roadmap.
One company. Three complementary AI directions.
Kvantim is building AI at three levels: a personal AI that lives close to its owner, a supervision layer that lets businesses delegate work safely, and a transformer model that can be trained for a specific domain. Different products, one company and one standard for control, teachability and honest product status.
The Kvantim ecosystem
Built by one team in Latvia · Shared product and deployment discipline · One status language across every site.
KvantimOne company, team & AI ecosystem
Kvantia AI
Working prototypePersonal AI
A personal AI that keeps chosen context close and grows through what you teach it.
Explore Kvantia AI Kvantia Harness
In early accessSupervised AI work
An AI worker that acts on real tasks without free rein, with a readable audit trail.
Explore Kvantia Harness Kvantim LLM
In developmentTrainable transformer
A classic transformer model rebuilt from an open-source base for further training and specialisation.
Discuss a model pilot
One strategy
AI becomes useful when capability, control and context come together
A capable model is only one part of a working AI system. A person needs continuity and privacy. A business needs permissions, approvals and proof. An organisation with specialist knowledge may need a model it can continue training instead of treating a general cloud model as fixed infrastructure.
Kvantim addresses those layers through three focused products. They are not three names for the same technology. They are three routes through one AI ecosystem.
| Need | Kvantim direction | What it changes |
|---|---|---|
| A personal AI that carries chosen context over time | Kvantia AI | From a generic session to a personal, local relationship |
| An AI worker that can act without unrestricted access | Kvantia Harness | From an ungoverned agent to supervised, reviewable work |
| A classic language model that can be trained for a domain | Kvantim LLM | From a fixed general model to a trainable transformer foundation |
Personal AI
Kvantia AI — a personal AI designed to live on your device
Status: Working prototype — the core interaction runs today under stated conditions; it is not yet a regular customer product.
For individuals who value privacy, continuity and the ability to shape their own AI over time.
Kvantia is being built to keep selected context, preferences and knowledge close to the person who creates them. Instead of treating every conversation as a fresh session with a remote generic model, it is designed around local operation, persistent memory and deliberate teaching.
- Personal and local-first, not a shared cloud persona.
- Memory intended to be visible and user-controlled.
- Teaching is explicit, not silent harvesting of conversations.
- Uncertainty is shown, not hidden behind confident language.
What works now: the core interaction runs as a working prototype. Persistent memory, teaching and wider device distribution carry their own In development or Planned status until they meet the shared definition.
Supervised AI work
Kvantia Harness — give an AI worker real tasks without giving it free rein
Status: In early access — the flow works for invited users, with explicit limits and team involvement.
For small and mid-sized businesses that repeat digital work but need human control over systems, credentials and irreversible actions.
Kvantia Harness turns a request into controlled execution. The AI receives a task, sees only the capabilities that routine requires, pauses sensitive actions for approval and returns the result with a readable audit trail.
- A task inbox and recurring routines.
- Permissions granted by capability.
- Human approval gates for defined actions.
- Credentials kept outside model context.
- Recovery and visible operational state.
- A complete record from request to result.
What works now: the web product can be seen and used through a private demo today. Native desktop applications are in development.
Trainable transformer model
Kvantim LLM — a classic model rebuilt to keep learning after the starting point
Status: In development — active implementation; it is not something you can rely on yet.
For organisations and technical partners that need a transformer model specialised for a domain, workflow, language or deployment requirement.
Kvantim LLM is a classic transformer-type model in the same broad category as other modern language models. It starts from an open-source model base, which the Kvantim team is rebuilding for further training and specialisation. The aim is not another fixed general chatbot — it is a model foundation that can be developed around defined data, evaluations and business requirements.
Before release, the public page will name the base model and its licence, state which components Kvantim has changed, and publish an evaluation method before using the word benchmarked. Specialisation tracks (analysis, office work, code, vision, local use) are intended directions inside Kvantim LLM, not six finished models.
Shared company advantage
Three routes to market, one learning organisation
- 01
Harness reveals real requirements
Business workflows show which permissions, approvals, integrations and evidence AI needs before it can do useful work.
- 02
The company compounds product and deployment discipline
Evaluation, control and deployment learning feed back into how every direction is built.
- 03
Kvantim LLM and Kvantia AI each advance a distinct frontier
Kvantim LLM develops trainable transformer capability; Kvantia AI pushes local operation, personal continuity and user-controlled learning.
- 04
Shared engineering, evaluation and go-to-market learning
The products stay distinct while the company compounds what it learns about trust, evaluation and useful AI.
Choose your route
Which direction are you looking for?
Delegate repetitive business work safely
See how Harness uses capability rules, approvals and an audit trail.
A model trained for a specific domain
Talk to Kvantim about the model base, training scope, data and evaluation.
Invest or partner across the ecosystem
See the company thesis, current evidence, milestones and use of capital.
Progress without ambiguity
What is available, what is being built and what comes next
One status language, used the same way on every Kvantim site.
| Direction | Current status | What that means | Next step |
|---|---|---|---|
| Kvantia Harness | In early access | The flow works for invited users, with explicit limits and team involvement. | Private demo |
| Kvantia AI | Working prototype | The core runs today under stated conditions; not yet a regular product. | Early access |
| Kvantim LLM | In development | Active implementation; you cannot rely on it yet. | Model pilot |
Evidence — a private demo, build notes or an evaluation summary — is shared on request rather than claimed on the page.
One ecosystem, the right entry point
Start with the problem you need AI to solve
Use the product that fits today, propose a model or deployment pilot, or talk to the Kvantim team about the wider ecosystem.