"Identity explains history. Intent explains now."
The most expensive visits in the world land on experiences that don't know they arrived - whether the visitor is human, LLM, or autonomous agent. InferKNOW closes that gap across all three simultaneously, in real time.
Every system today (CDPs, recommendation engines, A/B platforms) optimizes for who your user is. Their history. Their segment. Their tier.
None of them optimize for what situation they are in right now or for the autonomous agents arriving to shop your catalogue invisibly. The most expensive traffic in the world lands on an experience that doesn't know it arrived.
High-intent clicks die on static pages. Autonomous agents scrape and leave. The result: revenue left on the table at every touchpoint, across every visitor type.
Platforms rarely know who the user is and never what they need right now. Profiles lag. Situations shift. The gap between what your visitor needs and what your site shows them kills conversions at scale.
ChatGPT, Google AI, Claude, Perplexity shift where decisions get made. The highest-intent traffic in the world from LLMs, ads, and social arrives with AI-formed intent and lands on pages that don't know it came from an AI assistant.
Autonomous agents scrape data without informing you of their arrival. Their intent is different to human intent. Today, that intent is invisible and completely unmonetised across every digital estate.
Most platforms stop at the first signal. InferKNOW combines individual, situational, and agentic intelligence in a single sub-50ms inference before the page finishes loading, before the agent scrapes a line.
A single script tag. 48-hour deployment. No CDP. No engineering sprint. No dashboards.
Infers intent, context, channel, device, and psychological readiness from anonymous session signals in under 50ms. Runs at the CDN edge, before your origin server receives the request.
Sub-50msScores every session across individual and situational dimensions simultaneously. Builds no profile. Retains no data. The intelligence lives in the moment, not in a database.
Zero PIIAdapts pricing, discounts, copy, imagery, CTAs, and product display in real time, before the page finishes rendering. No A/B tests. No dashboards. Just the right experience, now.
Pre-renderStructures content for AI discovery. When buyers ask ChatGPT, Perplexity, or Google AI Overviews for recommendations, InferKNOW ensures your brand is cited and accurately represented.
AI DiscoveryCaptures high-intent behavioural data without a CDP. Builds a unified audience intelligence asset owned entirely by your brand no third-party dependencies and no cookie requirements.
1P DataConducts direct 1:1 negotiations with autonomous buyer agents on pricing, discounts, items, bundles, and upsells - closing sales faster while reducing latency and token usage for buyer agents.
Agent-to-AgentInferKNOW deploys as an edge layer. Your stack doesn't change. Your team doesn't need to be involved after day one.
A single JavaScript tag or server-side SDK. Integrates with any website, app, or commerce platform. No data pipeline rebuild. No migration from your existing stack.
~4 hours of engineeringInferKNOW begins scoring every session at the CDN edge - human visitors, LLM-referred arrivals, and autonomous agents - inferring intent, channel, device, and situational context before a single byte reaches your origin server.
Immediate · zero latency impactPricing, discounts, copy, images, CTAs, and product display adapt in real time for human and LLM visitors. The Agentic Engine negotiates directly with autonomous buyer agents to close sales before they scrape and leave.
Verified lift at day 30InferKNOW deploys across e-commerce, retail, media, fintech and more. The intelligence layer is vertical-agnostic. The outcomes are not.
A buyer arriving from an LLM with high purchase intent receives a PDP calibrated for their discovery context - not the same page a returning loyalty member with a replenishment need sees. And not the same data which is presented to a buyer agent. Each form of intent is structurally different, and demands an entirely different data hierarchy.
Real-time inference detects session depth, category engagement, and spend proximity to loyalty programme thresholds. The upgrade offer surfaces at maximum willingness to pay not at generic checkout prompts or automated email sequences.
InferKNOW connects the right person to the right ad at the exact moment of peak receptivity. Situational intelligence scores each session for category affinity, engagement depth, and purchase readiness ensuring sponsored content surfaces when intent is highest, not just when a keyword matches. Ad yield improves without increasing inventory or changing rates.
Routes reader intent from editorial content directly to financial product conversion in real time. A user spending 12 minutes reading about investment strategy becomes a product prospect automatically and instantly, without form fills or interruptions.
Situational Intelligence, not surveillance
InferKNOW does not build or store personal profiles. It interprets the live situation (channel, context, device, moment, intent signal) and acts on it instantly. No data is retained between sessions. No identity is tracked across visits. The intelligence lives in the moment, not in a database. This is not a compliance posture. It is the architecture. It is why InferKNOW works where CDPs, cookies, and legacy personalisation engines are structurally failing.
"I meet dozens of partners every week (retailers, enterprises, even governments) and I can't think of a single one that wouldn't adopt InferKNOW immediately. CDPs simply can't keep pace with this model."
Principal Industry Architect · Leading LLM Company
Sub-50ms intent scoring at the CDN edge was once a technical impossibility. Today, the infrastructure is mature enough to score intent and adapt an experience before the page even renders. The technology is here, but the market hasn’t yet moved. This is your window to own the speed advantage before it becomes the standard.
Legacy stacks - CDPs, A/B testing, and recommendation engines - are built on identity, or who a user was yesterday. But identity only explains history; intent explains now. There is currently no incumbent for the Situational Layer, the system that acts on the live moment. That position is open only until your competition realizes it exists.
Agentic buyers are already traversing your catalogue - scraping, evaluating, and abandoning without you knowing. You have no intelligence layer to detect them, negotiate with them, or control the sale. Every day without InferKNOW is revenue that leaves without a trace.
ChatGPT, Perplexity, Google AI, and Claude are now primary research channels for high-intent buyers. That traffic arrives primed to convert and hits static pages built for keyword-formed intent. The mismatch is structural. Your conversion rate is paying for it right now.