ByteLite LLC · Research and development · Helena, Montana, USA

Exact data.
Traceable knowledge.
Designed to distinguish evidence from uncertainty.

We build computing you can check: data that rebuilds byte for byte, and machine cognition designed to answer only from knowledge it can trace.

Ribbons of blue light flowing through a transparent lattice of glass panels.
Conceptual illustration An impression of ordered information. It is not a working system.

Evidence to date is internal. Nothing has been independently verified. No product is on sale, and checkout is switched off. How we label evidence

Tested in our labs

What works today.

Measured results from our own automated test runs. Each figure says exactly what it covers.

  • 4,515 / 4,515

    byte-exact rebuilds

    Every test encoding rebuilt exactly.

    Each one was decoded and matched to its original byte for byte before it was accepted. Separate 8 MiB and 64 MiB files also rebuilt exactly.

    Stage: tested in-house. Compression release of 12 October 2026, one machine, 301 small test inputs. Exact rebuilding is not compression: every output was larger than its input. For example, a 4,096-byte text sample became 15,541 bytes, and a separate 67,108,864-byte (64 MiB) test file became 301,984,168 bytes. Effective compression has not been demonstrated.

  • 4,758 / 4,758

    automated checks passed (Release run)

    An owner-certified test run of one release.

    In the recorded Release run, all 103 test suites passed, including all 4,758 checks. The Debug run also passed 103 of 103 suites; its check count is not claimed here.

    Stage: tested in-house. Cognition release of 15 October 2026, certified for build and automatic tests only, one machine. It is not the current development branch, which is newer and not yet certified. Tests that need large language collections were not exercised.

  • By design

    gaps reported, not filled

    Designed to say what it does not know.

    When nothing is on record about a concept, the system replies that it does not know and asks for more information rather than inventing an answer. This holds in the cases our tests cover.

    Stage: tested in-house, tested cases only. Cognition release of 15 October 2026. Not yet shown for every phrasing: handling of ambiguous input and the grounding of claims in replies are still being completed.

  • 39 / 39

    trace checks passed

    Designed so answers carry their source.

    Answers drawn from knowledge are built to carry the record they came from, its stated source and its status, and each request runs against one fixed, recorded knowledge version.

    Stage: tested in-house. Cognition release of 15 October 2026, 39 trace checks. Sources are recorded as supplied. How strongly a record is labelled as established, and how a source is matched to a claim, are being tightened, so traceability is not yet shown for every answer.

  • 16,777,216

    colours matched, six field computations

    Accelerated colour-field paths match the reference exactly.

    The accelerated paths (SSE4.1 and AVX2) gave byte-identical results to the reference path for every possible 24-bit colour, in each of six colour-field computations.

    Stage: tested in-house. Vision release of 10 October 2026, one machine. This covers six colour-field computations, not image processing in general. Synthetic and test images only.

  • 213 / 213

    architecture-level tests passed

    Audio foundation in place.

    The audio research architecture passed all 213 of its tests.

    Stage: tested in-house. Audio architecture release of 10 October 2026. Architecture-level testing only: no speech, music or audio analysis yet.

Research programs

Three programs. One standard: prove it.

Machine Cognition

Building AI designed to answer only from knowledge it can point to, and to say "I don't know" rather than guess.

Tested
Governed request handling, sourced knowledge records, fixed knowledge versions and operator-only teaching.
Next
Understanding how the parts of a request relate, then matching them to established knowledge.
Explore Machine Cognition →

Data Representation

Representing data so it rebuilds exactly, byte for byte, every time, with every byte accounted for.

Tested
Exact byte-for-byte reconstruction and identical output on repeated runs.
Next
A complete representation measurably smaller than its input on a declared test collection.
Explore Data Representation →

Visual and Audio

Describing images and sound in exact, repeatable structures that other systems can rely on.

Tested
Deterministic image-structure components on synthetic test images.
Next
The remaining image behaviours implemented, then results on real-world images.
Explore Visual and Audio →

Where it is going

How the programs fit together.

  1. Information

    Preserve information exactly and describe it in structured, repeatable forms.

  2. Understanding

    Establish what is known, how concepts relate, and what is still missing.

  3. Governance

    Keep behaviour inside explicit constraints, with provenance and validation.

  4. Applications

    Products may use research results only after they are validated.

Conceptual illustration The intended long-term relationship between the research programs. These integrations do not exist today.

Test our claims.

Independent evaluators, research partners and licensees: pick a result and check it under your own conditions.