made. Signal

Make your platform the answer the engines recommend.

A semantic search and Generative Engine Optimization platform — made to map how conversational AI engines and traditional search interpret your category, and to position your business as the recommended answer. Every recommendation arrives with its source query and citation attached — traceable evidence, not unattributed prediction. For growth directors, SEO strategists, and digital performance leads.

Book a conversation

Frequently Asked Questions

What exactly is Generative Engine Optimization (GEO)?

GEO is the discipline of structurally engineering your public content so that conversational AI engines and large language models can ingest, attribute, and recommend it. Traditional SEO optimises for blue-link ranking on a search results page. GEO optimises for being inside the answer the AI engine gives — the citation, the source, the recommended option. As buyers increasingly ask AI engines directly for vendor and product recommendations, GEO is becoming the dominant determinant of category visibility.

How does it relate to traditional SEO?

made. Signal covers both. Traditional search rank still drives meaningful volume, and the structural work that wins citation inside AI engines tends to lift traditional search too — clean schema, answer-shaped content, topical authority, credible sourcing. We treat them as the same problem viewed through two surfaces, and made. Signal optimises and measures for both in one workflow.

How does it relate to made. Engine?

A closed loop. made. Signal listens — mapping how AI engines and traditional search understand your category, and surfacing the topics your market is actively asking for. made. Engine answers — turning those topic briefs into brand-governed, multi-channel content. The market's response feeds back into made. Signal, and the cycle tightens. Each runs as a standalone platform; together they close the discovery-to-content loop.

Can it monitor competitor visibility too?

Yes. Competitive share-of-voice across both AI engines and traditional search is tracked alongside your own footprint. made. Signal decomposes the topical coverage that's earning competitor visibility, identifies where they're being cited inside AI answers ahead of you, and quantifies the cost of each gap. The output is actionable — which specific concepts, formats, and assets to publish in response.

How does the made. Ledger apply to made. Signal?

Every recommendation, citation-share reading, and intent signal made. Signal surfaces is logged on the made. Ledger with the source query, the engine it came from, and the telemetry timestamp that produced it. That means board-ready discovery reporting carries an immutable provenance trail, competitor share-of-voice claims are defensible, and any output your growth team acts on can be traced back to its evidence on demand.

How is our data handled?

made. Signal runs on the same sovereign architecture as every made. Platform. Your strategy data, competitor analyses, and discovery telemetry are tenant-isolated, Australian-hosted, encrypted at rest, and never used to train external public models. Where inference runs off-shore, it runs only on Zero Data Retention providers. See the shared architecture.

Discovery has shifted. Most keyword strategies haven't caught up.

For the growth director

Intent-driven buyers no longer just browse blue links. They ask conversational AI engines for direct software, vendor, and service recommendations — and act on the answer. If your platform isn't being cited inside those answers, you are invisible to the buyers who are furthest down the funnel.

For the SEO strategist

Traditional keyword optimisation rewards a single channel that's losing share every quarter. Semantic authority — how AI engines understand your category, your offering, and your credibility — is what now decides visibility. The playbook needs to change before the traffic does.

An autonomous market visibility and search strategist.

made. Signal continuously crawls the digital landscape — conversational AI engines, traditional search, competitor footprints — and builds a programmatic blueprint that positions your platform as the recommended answer when buyers go looking.

01

Generative Engine Optimization (GEO)

Be the cited source inside AI answers

made. Signal structurally formats your public documentation, product pages, and thought leadership so conversational AI engines and LLMs consistently cite, source, and recommend you. When a buyer asks an AI engine for solutions in your category, your platform is in the answer.

Key Benefits
  • Structured-data, schema, and citation surface engineered for AI ingestion
  • Answer-format content guidance — what AI engines actually reward
  • Citation tracking across major LLMs — measure recommendation share
  • Cross-channel uplift — traditional search benefits from the same restructuring
02

Topical Authority Mapping

Know exactly what to cover, and why

made. Signal analyses competitor digital footprints, decomposes their topical coverage, and identifies the informational gaps in your own. It tells you precisely which concepts your site must own to dominate the category — and which are diluting your authority right now.

Key Benefits
  • Competitor footprint decomposition — what they cover, what you don't
  • Topic-gap prioritisation against business value, not raw search volume
  • Cannibalisation detection — pages diluting your own authority
  • Briefs feed straight into made. Engine for content production
03

Market Intent Listening

Make the trend yours before it peaks

made. Signal continuously monitors shifts in industry search patterns, conversational queries, and online sentiment. Your growth team gets real-time signals on what your market is asking — early enough to deploy a campaign before the trend tops, not after.

Key Benefits
  • Conversational query monitoring across major LLMs
  • Traditional search trend detection with rising-velocity alerts
  • Sentiment shifts tracked across forums, social, and trade press
  • Topic briefs handed straight to made. Engine for response
04

Discovery Performance Telemetry

See where you land in every engine

Track how often your platform is surfaced in conversational AI answers, how it ranks across traditional search, and how that footprint moves week-over-week. The metric that actually matters — being the recommended answer — is finally measurable.

Key Benefits
  • Citation-share tracking across the major conversational AI engines
  • Traditional search position monitoring on the queries that convert
  • Competitive share-of-voice across both surfaces
  • Board-ready reporting on discovery performance and ROI

How it works

01

Map your footprint

made. Signal indexes how AI engines and traditional search currently understand your platform, your category, and your competitors.

02

Identify the gaps

Topical authority is mapped, competitor coverage you don't match is surfaced, and the cost of each gap is quantified.

03

Build the blueprint

A concrete content and technical optimisation plan is generated — what to publish, what to restructure, what to retire — calibrated to AI engines and search.

04

Measure and adapt

Discovery performance is tracked continuously. Emerging intent shifts route to your growth team — and to made. Engine for content response.

What changes

made. Signal handles:

  • Continuous footprint mapping across AI engines and traditional search
  • Topical authority gap analysis versus competitors
  • Real-time market intent monitoring
  • Programmatic blueprints — publish, restructure, retire
  • Discovery telemetry across LLMs and search

Your team is freed for:

  • Strategic positioning — which categories to own
  • Creative narrative work, channelled to what made. Signal says will land
  • Executive thought-leadership where it actually moves the dial
  • Building the credibility made. Signal measures
  • Acting on intent signals before they become competitive

made. Signal doesn't replace your growth team. It makes the architecture of discovery legible — so they can compete on judgment, not guesswork.

What you get

Cited, not just crawled

Your platform is structurally engineered to be sourced by conversational AI engines — not buried under aggregator and review-site recommendations.

Trend-leading, not trend-following

Intent shifts get to your growth team before the trend peaks — and route automatically into Engine for content response while the window is open.

Measurable visibility

Recommendation share inside AI engines is tracked alongside traditional search rank. The metric that actually drives modern buyer behaviour finally has a number.

Runs on the made. Ledger

Every recommendation, gap analysis, and intent signal made. Signal surfaces carries the source query, citation, and engine telemetry that produced it — so your growth team acts on traceable evidence, not unattributed prediction.

Make your platform the answer.

Book a conversation