Platform

Every capability, organised by the loop it serves.

From the first prompt set to the re-measurement that proves a change. Real screens from a live tenant; no mock-ups.

platform.agent-lens.ai · tour

Growth Cockpit → measurement scope → Diagnose → Treatment → Artifacts → Brand Management, in 24 seconds. Muted; plays when in view.

Stage 1 · Configure

Three ways in. Every path lands in the same durable pipeline, so the stage survives restarts, devices and sessions.

System Prompts: Measure the governed prompt set saved for your sector and brand: Turkish banking ships 168 prompts across retail, SME and corporate segments.
Custom Prompts: Ask ad-hoc questions without touching the saved taxonomy. The right way to test a campaign or a product launch.
Data Feeding: Audit a product feed (CSV, JSON, XML) with no crawling at all, for sites that block crawlers or catalogs that have not shipped yet.
Brand Management: Version your prompts, sector rivals, AI surfaces and cadence. Saving creates a new prompt-set version and never rewrites history.
Prompt taxonomy: Recommendation, research and comparison intents, scoped by customer type, product family and channel, so results can be sliced later.

platform.agent-lens.ai/brands

Brand Management: the governed prompt set, versioned on every save.

Stage 2 · Measure

Five surfaces: ChatGPT, Claude, Gemini and Grok through their vendor APIs, plus Google AI Mode read as a live search surface.
Estimate → confirm → run: A spend-free estimate with pinned models, expected calls and a hard cap at 115%. A run exists only with a current, single-use estimate and your confirmation.
Smallest detectable change: The estimate states the least week-over-week movement the run could confirm, so you never buy a benchmark that cannot answer the question.
Variance control: Multi-trial averaging, pinned model versions, deterministic sampling and a 95% confidence interval on every metric.
Bring your own keys: Save, test, rotate and delete OpenAI, Anthropic, Gemini and xAI keys. Encrypted at rest; owners and admins only.

Stage 3 · Diagnose

Smart crawler: Sitemap discovery, two-stage sampling, a 7-tier fetch cascade for WAF-protected sites and optional headless rendering for JS-heavy pages.
Schema & content audit: Per-page JSON-LD extraction and validation, semantic HTML scoring, meta quality and llms.txt detection.
AI bot access check: Detects whether GPTBot, ChatGPT-User, ClaudeBot, PerplexityBot and Googlebot are blocked in robots.txt.
Evidence map: A full causality trail from every score back to the page, tag or model answer that produced it.
History & diff: Audit history, snapshot comparison, added and removed page detection, per-audit token and cost tracking.
Action queue: Ranked, evidence-backed work items assembled from what the pipeline recorded, not a generic checklist.

Stage 4 · Improve

JSON-LD generator: Complete structured-data blocks for the pages that lack them.
llms.txt generator: A spec-compliant file for your root, built from brand identity and the crawl manifest.
robots.txt fixer: Unblocks the AI crawlers you want and keeps the ones you do not.
Meta tag optimiser: Title, description and Open Graph tags rewritten for the page.
Semantic HTML audit: Pattern detection plus fix snippets for the markup agents read.
Fact-Feel-Proof rewriter: Three-block product descriptions written for model comprehension.
Doc2Query++: Synthetic queries plus FAQPage JSON-LD, so the page answers the questions people ask assistants.
Image audit & attributes: Missing-alt detection with AI captioning, and inferred attributes enriched into your JSON-LD.

LLM-assisted drafting runs on your own provider key or the platform model plane. Measurement never does.

Stage 5 · Integrate

Input

Your crawled catalog

Product pages, attributes, relationships and prices as the audit recorded them.

Also generated

OpenAI
ACP
Agentic Commerce Protocol
ACP-compliant JSON + TSV product feeds, validated.
Google
UCP
Universal Commerce Protocol
Merchant Center JSON + XML with conversational attributes.
Anthropic
MCP
Model Context Protocol
Docker-ready Python MCP server, scaffolded and downloadable.

ACP · OpenAI: ACP-compliant JSON and TSV product feeds with validation.
UCP · Google: Merchant Center JSON and XML with conversational attributes.
MCP · Anthropic: A Docker-ready Python MCP server, scaffolded and downloadable.
Relationship tagger: Substitute, accessory and cross-brand relationships across your catalog.
Agent-first API: An OpenAPI spec plus a FastAPI sample you host, so agents can query your catalog directly.

Stage 6 · Govern

Automations: Scheduled re-measurement delivered to Slack, Microsoft Teams, email or a webhook, with an alert inbox. Each cycle runs under its own hard cap; one that would exceed it is refused.
Alerts that survive a significance test: A week-over-week drop reaches high severity only when a two-proportion test rejects noise at α 0.05. A real drop names its metric in the subject line.
Sources to earn: Cited sources that informed answers naming a rival but not you: a ranked, exportable list of places to get listed.
Benchmark exploration: Slice visibility and comparison results by scope, topic, intent, provider and active rival pool. Dashboard and report filters agree.
Exposure ledger & snapshots: Portfolio trends, per-brand breakdown, weakest and strongest pillar; immutable report snapshots as PDF, PPTX, XLSX and JSON.
Sector catalogs: Turkish banking (47 banks, tiered rival pools) and fashion (99 tagged brands) today. Fintech, tech & electronics and lodging as approved packs.

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