Be in the agent's candidate set the moment it retrieves.
When a human asks Claude, ChatGPT, Gemini or Perplexity "what's the best X," the agent retrieves a candidate set in seconds — from its training data, citations it trusts, and tool registries it can read. Introduce is about being in that set. It is not human SEO or AEO — that's a different problem, and a different vendor (we refer customers to Teknicks).
The problem
The candidate set is built before any human ever scrolls.
The human used to type a query, scan ten blue links, and build a shortlist. Now they ask an agent and the agent does the retrieving — pulling from what's already in the model, from sources the agent cites, and from machine-readable surfaces it can fetch directly (MCP, well-known endpoints, structured pricing, schema). If you're not in that retrieval pass, the human never sees your name. Human-funnel SEO and AEO don't fix this; they're a different layer.
Our thesis
ALG360 measures whether the agent retrieves you for the prompts your buyers actually use, shows you why it doesn't when it doesn't, and ships the structured, machine-readable surfaces that get you into the candidate set on the next pass.
buyer prompts tracked weekly
frontier models monitored
to measurable retrieval lift
What's inside
Capabilities that ship in the product.
Agent Readiness Scan
Runs the prompts your buyers actually use against the frontier models and shows whether the agent retrieves you, who it retrieves instead, and which signals (citations, schema, tool registries) it weighted to get there.
Frontier-model retrieval tracking
Weekly retrieval share for you vs. competitors across hundreds of buyer prompts in Claude, ChatGPT, Gemini and Perplexity — trended over time so you can see what's moving you in or out of the candidate set.
Machine-readable product surfaces
Structured product, capability and comparison data the agent can grab in a single fetch — schema, well-known endpoints, and a canonical capability index that frontier-model retrievers reuse.
Tool-registry & MCP discovery
Get listed where agents look first: MCP registries, the .well-known/mcp directory, and the integration directories the agent reads when scoping who it can act with.
Citation footprint in agent-trusted sources
Identify the 30–100 sources the agent disproportionately cites for your category and ship the structured reference content (docs, comparisons, capability briefs) those sources want to link.
Human-funnel SEO/AEO — referred to Teknicks
ALG360 deliberately does not do human SEO/AEO. When the Scan finds weak human-funnel signals, we refer you to Teknicks, the AEO specialists we trust for that work. It's a separate engagement; we don't take a fee.
How it runs
From signal to compounding.
- Day 1
01. Run the Scan
Point ALG360 at your domain and ICP. Within minutes you see whether agents retrieve you for the prompts that matter — and the top fixes.
- Week 1
02. Retrieval baseline
Track retrieval share across hundreds of buyer prompts on every frontier model. Benchmark vs. three competitors.
- Week 2–4
03. Ship the fixes
Work through prioritized Introduce findings — schema, structured pricing, capability index, MCP discovery — and re-scan as you publish.
- Ongoing
04. Compound
Weekly retrieval deltas, prompt-set expansion, and net-new structured surfaces where the gap is widening.
Inside the pillar
The shortlist version.
- Agent Readiness Scan — what the agent finds when it retrieves your category
- Training-data, citation and tool-registry presence in the sources agents trust
- Machine-readable product, pricing and capability data the agent can grab in one fetch
Outcome
Named by Claude, ChatGPT, Gemini & Perplexity when the agent retrieves vendors.
Stack
- Agent Readiness Scan
- Retrieval Tracking
- Schema.org
- MCP / .well-known
- Frontier-model retrievers
"Claude Code recommends Resend over SendGrid 63% of the time. That's not a marketing win — it's the agent retrieving Resend first. Introduce is how you become the candidate it returns."
FAQ
Pillar questions, answered.
- Isn't this just SEO or AEO?
- No. SEO/AEO optimize human-facing search surfaces — Google, Perplexity, AI Overviews — where a human reads the result. Introduce optimizes the agent's retrieval pass: what's in the model, what the agent cites, what it can fetch deterministically (schema, MCP, structured pricing). Different signals, different surfaces. If you need human-funnel AEO, we refer to Teknicks.
- Why do you refer SEO/AEO out?
- Because it's a crowded specialty and not what ALG360 is built for. We focus the product on the agent side — retrieval, evaluation, execute. Teknicks runs the human-funnel AEO/SEO work for our customers. It's a clean handoff, no revenue share, no co-branding.
- How fast do results show up?
- Retrieval changes (agents fetching new schema, MCP endpoints, citations) show in 2–6 weeks. Training-data shifts compound across model generations — typically one to two quarters before you see them in base-model behavior.
- What if my category isn't being researched in LLMs yet?
- Then you have a window to own the retrieval surface before competitors notice. Most B2B categories are still under-defended inside frontier models.
See where you stand on Introduce.
The Agent Readiness Scan benchmarks you on every pillar — including this one — and ships the exact fixes that move the needle.