Design System

One standard, applied everywhere.

The shared language behind every Ioma Labs page — surfaces and ink, the five-layer palette, the type system, spacing, components, and the copy register. Built as plain tokens, CSS, and writing rules so the marketing site, internal docs, and product surfaces all read as one thing.

01 — Color

Cool, clinical paper.

A muted paper neutral rather than the default warm cream, near-black ink, one schematic blue, one annotation amber — and five layer colors that carry the architecture through every diagram on the site.

Surfaces & ink

Paper
--paper
#F5F6F1

Default page background.

Raised
--paper-raised
#FFFFFF

Cards and raised surfaces.

Sunken
--paper-sunken
#ECEEE6

Footer, wells, table heads.

Ink
--ink
#15191E

Primary text, dark bands.

Ink soft
--ink-soft
#51585F

Body & secondary copy.

Ink faint
--ink-faint
#8B9097

Captions, meta, labels.

Rule
--rule
#DCDED5

Hairlines & grid lines.

Rule strong
--rule-strong
#C5C8BC

Emphasised dividers.

Brand accents

Schematic blue
--accent
#2B3F8C

Primary accent. Links, eyebrows, active states.

Accent ink
--accent-ink
#1E2C63

Pressed / deep accent.

Accent soft
--accent-soft
#E6E9F4

Accent tint fills.

Annotation amber
--amber
#B9722A

Secondary accent. Status, flags.

Amber soft
--amber-soft
#F3E4CF

Placeholder-tag fills.

The five-layer palette

01 · Mesh
--layer-mesh
#A97D49

Knowledge mesh — stored facts.

02 · Relations
--layer-relations
#5E7F73

Relation mesh — typed edges.

03 · Language
--layer-language
#5A6F99

Lexicon, grammar, and order.

04 · Answer
--layer-answer
#2B3F8C

The spoken, provenance-carrying answer.

05 · Feedback
--layer-feedback
#8B6B8D

Graded feedback — the teaching loop.

Layer colors are fixed: a stage of the teaching turn is always the same hue wherever it appears — diagram, chip, dot, or the identity strip at the top of every page. The old tier tokens (--tier-*) remain as deprecated aliases; do not use them in new work.

02 — Type

Three voices, clearly divided.

A structural display face for headings, a serif for body copy that gives the writing field-notes gravitas, and a monospace reserved strictly for labels, eyebrows, and data annotation.

Ag
Halogen
Display · headings

Falls back to Archivo until the licensed Halogen files are dropped in. Weights 700 / 800.

Ag
Source Serif 4
Body · long-form

Optical-sizing on. Regular, Medium, Semibold + italic.

Ag
IBM Plex Mono
Labels · data

Eyebrows, rail labels, tier chips, captions. Uppercase, tracked.

Type scale

Display 4XL--text-4xl
clamp 2.6–4.4rem
A different kind of intelligence.
Display 3XL--text-3xl
clamp 2.1–3rem
One mechanism, three layers.
Display 2XL--text-2xl
clamp 1.6–2.15rem
Relations & graded feedback
Lede LG--text-lg
1.15rem · soft ink
Every belief carries a strength, a hit count, a confirmation flag, and a tutor attribution — the entire belief state can be opened and read by a human.
Body Base--text-base
1rem · 1.6 line
Relations are stored as independent records, so confirming or rejecting one cannot disturb another. Disentanglement is structural, not a training trick — this is the seam in the system we can most directly inspect.
Mono label XS--text-xs
0.75rem · tracked
01 — Architecture
03 — Spacing

An 8-pixel rhythm.

Spacing steps from an 8px base; corners stay nearly square; structure is drawn with hairlines, not shadows. Whitespace is generous and consistent across every page.

Spacing scale

--s-18px
--s-216px
--s-324px
--s-432px
--s-548px
--s-664px
--s-788px — section padding
--s-8120px

Rules & radius

Hairline

1px rules

Sections, cards, and tables are separated by 1px --rule lines. Grids show the rule color through 1px gaps.

Radius

4px, sparingly

Corners stay near-square (--radius: 4px). The drafting feel comes from straight edges, not rounding.

Container

1240px max

Content caps at --maxw with a 92px annotation rail on the left at desktop widths.

04 — Components

The shared parts.

Every page is assembled from this small, consistent kit. Hover to see the interaction states.

Buttons

Mono uppercase labels · 1px ink border · primary fills to accent blue on hover.

Tier chips & eyebrow

Research Layer 01 Correctable Teaching phase Placeholder

Cards

Layer 01

Knowledge mesh

Facts stored as explicit chunks with individual strength scores — retrieval ranks by similarity × strength, and nothing is reconstructed from weights.

Layer 02

Relation mesh

Typed edges between facts, held as independent records. Confirming or rejecting one relation cannot disturb another.

Layer 03

Language layer

A learned lexicon and a rule-first grammar — vocabulary is earned through teaching, never imported.

Callout

A weak answer is correctable; a refusal teaches nothing. Once seeded, the system always answers with its best attempt — because the output exists to be graded.

— Ioma Labs, design principle

Comparison table

DimensionPretrained modelResonance
Where knowledge livesEntangled in the weightsAn explicit, human-readable store
Fixing a wrong factA retraining cycleOne graded correction
ProvenanceRetrofitted, approximateStructural — answers trace to their sources

Roadmap / timeline

  • Hardened — July 2026

    Full-build stress test passed

    Four critical defects found, fixed, and measured; retention under new learning verified with rehearsal replay.

  • Now — First domain

    Stand up the board of experts

    The learning curve and held-out generalization numbers publish as they accrue.

05 — Schematic

The signature element.

A literal cross-section of one teaching turn — the knowledge mesh at the base, confirmed relations, the learned language layer, the spoken answer at the top, and graded feedback looping back into every layer. Numbered, because here the sequence is real, not decorative. Reused at different scales across the site.

Architecture motif — drawn at small scale

A standalone diagram motif — the same stack abstracted: mesh, relations, answer at the apex. Used in figures, not beside the wordmark.

Full interactive schematic

Lives at hero scale on the home page — hover any stage to highlight it and read what it does.

07 — Copy

One voice, written down.

The register every page is written in — drawn from the way serious AI research labs write about their own systems: plain, exact, and calibrated, never promotional. This is the source of truth for copy. When the company and product details are finalized, the words change; these rules do not.

The voice in one line

We write like a research team describing its own work to a careful reader — declarative, specific, and honest about the edges. We explain the system; we do not sell it.

— Ioma Labs, copy register
Tone

Plain & exact

Short declarative sentences. Subject, verb, object. The next sentence earns its place or it's cut.

Stance

Calibrated

Claims are sized to the evidence. We hedge where we should and admit what we don't yet know.

Posture

Unsold

No hype, no superlatives, no urgency. The architecture is interesting on its own terms; we describe it.

Six principles

01

Write declaratively

State what is true in the simplest order. Prefer the active voice and a concrete subject. Cut throat-clearing — "it's important to note," "in today's landscape."

02

Size claims to evidence

"Early testing shows," "we're hopeful," "this can fail" are features, not weakness. A measured claim a reader can trust beats a bold one they can't.

03

Define before you use

Introduce a term in plain words the first time it appears, then use it consistently. Expand an acronym once; never assume the reader arrived mid-thought.

04

Show, don't sell

Ground every abstract claim in something concrete — a number, an example, a diagram. If a sentence can't be made specific, it probably isn't true enough to keep.

05

Say what it is and isn't

The clearest framing draws a boundary. "An architecture layer, not another model." Naming what something is not is often the fastest way to say what it is.

06

Admit the edges

Give limitations their own space rather than burying them. A page that names its own open questions reads as more credible, not less.

Register by surface

Each part of the type system carries a different writing job. Match the words to the surface.

SurfaceIts jobExample
Display headingOne idea, terse, often a boundary. Sentence case with a terminal period — the house signature.Architecture, applied.
LedeOne paragraph that frames the section in plain language. Says what this is and why it matters.Tessera sits between the people who ask and the systems that hold the answers.
BodyThe argument, in serif. Declarative sentences, concrete examples, the occasional em dash for an aside.Specialist outputs are combined through a fixed, repeatable procedure — the same inputs produce the same state.
Mono labelEyebrows, rail tags, chips, captions. Uppercase, tracked, two or three words at most.01 — ARCHITECTURE
CaptionAnnotates a figure. Mono, factual, no salesmanship. Reads like a lab note.FIG. 2 — TESSERA DEPLOYMENT TOPOLOGY
ButtonA plain verb phrase for the action. No exclamation, no manufactured urgency.Get in touch

Rewrites — before & after

Instead ofWriteWhy
Revolutionary AI that supercharges your entire organization.A reasoning layer over the systems you already run.Hype replaced with what it actually does.
Our model crushes the competition on every benchmark.On Terminal-Bench 2.0, it scores higher than any model we tested.A named, checkable claim instead of a boast.
Seamlessly unlock the limitless power of your data!Your data stays where it is and becomes answerable in plain language.Concrete benefit; the exclamation and "limitless" are gone.
It just works, like magic.Reasoning runs as discrete steps, so each one is inspectable."Magic" is the opposite of inspectable — say the mechanism.

Words

Use

Plain, structural, exact

  • architecture, layer, system, endpoint — the literal nouns of the work
  • inspectable, deterministic, grounded, calibrated — properties we can defend
  • we find, early testing shows, this can fail — honest framing of evidence
  • is / isn't, does / doesn't — boundaries that define by contrast
Avoid

Hype, vagueness, urgency

  • revolutionary, game-changing, cutting-edge, next-gen — empty intensifiers
  • seamless, magical, effortless, limitless, unlock, supercharge — marketing filler
  • world-class, best-in-class, leading — superlatives without a benchmark
  • exclamation marks, emoji, and manufactured urgency — none, anywhere

Claims & evidence

Qualify

Date and attribute

Tie a claim to its source and moment — "in our internal evals," "as of this release." An unqualified superlative is a liability.

Compare

Name the comparison

If something is better, say better than what, measured how. "Higher on BrowseComp than the next model" — never a bare "the best."

Hedge

Hedge honestly

"Could," "we're hopeful," "early signs suggest" are permitted and encouraged where the evidence is partial. Precision about uncertainty is a feature.

Mechanics

Case

Sentence case

Display headings are sentence case and end in a period. Eyebrows, rail labels, chips, captions, and buttons are UPPERCASE, tracked. Never title case.

Punctuation

The em dash

Spaced em dashes carry asides and definitions in body copy. No exclamation marks. Serial comma on.

Numbers

Numerals for data

Spell out small cardinals in prose ("five stages," "three voices"); use numerals for measurements, scores, and tokens. Keep units tight to the figure.

Canonical lexicon — source of truth

The approved spelling and use of every proper noun on the site.

TermUse it forWrite it as
Ioma LabsThe company. An AI research company building Resonance; Tessera is its applied integration practice.Ioma Labs in prose. The wordmark sets uppercase; copy never does. Legal: Ioma Labs, LLC.
ResonanceThe system — a from-scratch, feedback-trained memory and language system. No pretrained model inside, no corpus.Resonance. Built, hardened, and live; in the teaching phase. Referred to as "it," never "she."
TesseraThe applied practice — compliance-native AI systems integration for regulated and mission-critical environments.Tessera. Available now, as subcontract and teaming engagements.
CalliopeThe earlier prototype's name, returning as the first taught personality of Resonance in the commercial release.Calliope. A personality of Resonance, not a separate system. Past tense for the prototype.
The five layersThe stages of a teaching turn. Each is a fixed name and a fixed color, everywhere.01 Mesh · 02 Relations · 03 Language · 04 Answer · 05 Feedback
The board of expertsThe teaching model: domain specialists set each field's skeleton and approve the automated curriculum that fills it.Lowercase in prose: the board of experts.
The learning curveThe honest instrument: capability as a function of corrections delivered, read against frontier performance on the same tasks.Lowercase in prose: the learning curve.

One system, end to end.

See it applied across the live pages — or read the architecture this whole visual language is built around.