A different mathematics for intelligence.

Litmous AI is built to make useful intelligence possible without requiring enormous pretrained models or specialised GPU infrastructure. Knowledge becomes structured and addressable, cognition follows selective mathematical paths, and useful transformations can be retained and reused.

Get Litmous AI

V1.0 launches first on Windows.
Additional platforms will follow.

Δ = Y ⊙ X̄ X → Δ ⊙ X → Y

c(x) ∈ ℂᵈ B(x,y) = c(x) ⊙ c(y) c(x) ⊙ c̄(x) = 1 ΔA→B = B ⊙ Ā

Represent the state. Derive the change. Reuse the change.

Litmous operates in a mathematical domain where identity, relationships and transformations can be represented directly. Shared structure can cancel, exposing the change between two compatible states. That change becomes a reusable operator, and it can be applied selectively rather than forcing the entire system through another dense computation.

B(x,y) = c(x) ⊙ c(y)

Exact identities are represented through complex phase carriers. Elementwise multiplication provides a native binding operation, while conjugation supplies the inverse. Meaning can therefore be composed and separated mathematically.

Δ_A→B = Y ⊙ X̄

When two states contain shared context, that common structure can cancel. What remains is the transformation between them. Litmous can retain the transformation itself rather than recomputing the original problem every time.

S′ = S + (Δ − I)P_R(S)

Cognition does not need to alter an entire structure when only one relation is relevant. The selected component is transformed while the surrounding state is preserved. Computation follows the part of the problem that actually requires computation.

The size of what Litmous knows does not have to become the size of every question.

INPUT

→

CORE

↔

PACKS · SKILLS · KNOWLEDGE

→

OUTPUT

Knowledge is separate from cognition.

Litmous does not need to carry the world's knowledge inside one enormous computational model. Persistent knowledge can exist independently and remain available for reuse.

Only relevant knowledge becomes active.

Exact identities and sparse routes allow the working state for a question to remain bounded even while the persistent knowledge available to Litmous continues to grow.

Computation follows the work.

The architecture is designed around selective cognition and reusable structure, making CPU, memory and inexpensive storage the normal execution environment rather than a fallback for unavailable GPUs.

Litmous does not need to know everything. It needs to understand what you give it.

Give Litmous documents, books, policies, procedures, technical material or other sources that matter to your work. It builds reusable understanding from that material and answers from the knowledge it has learned. When the information required for an answer is not available, unsupported knowledge is treated as a limitation rather than something to invent.

CPU.
Memory.
Storage.

Litmous is designed to operate where the user's work already lives, using ordinary computing resources and locally retained knowledge rather than requiring every task to be sent to a specialised remote computing cluster.

Litmous AI.
On your computer.

Litmous AI V1.0 will be released first for Windows. The architecture is not tied to Windows: support for additional desktop and mobile platforms will follow as Litmous develops beyond its initial release.

Initial release
Litmous AI V1.0
Windows

Installer coming soon