Define the categorybefore someone elsedefines it for you.

Embedded AI engineering

Also known as
Forward-deployed AI engineering · Embedded engineering

A delivery model where AI engineers work inside a client's stack to build production systems the client owns at the end.

Embedded AI engineering is a delivery model where AI engineers are forward-deployed inside the client's environment, working alongside the in-house team for the duration of an engagement. The deliverable is a production AI system built bespoke for that client's data, workflows and operational metrics. Ownership transfers to the client. This is the opposite of off-the-shelf SaaS (where every customer gets the same product) and remote consulting (where the deliverable is a deck, not software). 2PT operates as an embedded AI engineering firm vertically specialised in marketing.

Forward-deployed engineer (FDE)

Also known as
FDE · Embedded engineer · Solutions engineer

An engineer who works inside the client's environment to build software solving a specific operational problem.

A forward-deployed engineer works in-situ at the client, with access to the client's systems, data and stakeholders, building software against the client's actual operational reality. The term was popularised by Palantir and is now used by Anthropic, OpenAI partner firms and embedded AI engineering teams. FDEs trade product breadth for delivery depth: they ship one system, deeply integrated, that solves one company's problem. Not a horizontal SaaS for everyone.

Production AI

Live AI software running inside real workflows with real spend, users and consequences. Not a pilot or demo.

Production AI is live software running inside a client's real workflows with real spend, real users and real consequences. It is distinct from a pilot (scoped test, no production traffic), a proof of concept (working demo, no integration), or a slide deck (intent, no system). 2PT only ships production AI. Every engagement ends with the system live inside the client's stack and the client's team operating it.

GEO (Generative Engine Optimization)

Also known as
Generative AI SEO · AI search optimization · LLM SEO

Structuring content and schema so a brand is cited by generative AI search engines like ChatGPT, Claude and Perplexity.

Generative Engine Optimization (GEO) is the practice of structuring a brand's content, schema and citations so the brand is selected and cited by generative AI search engines. ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews. SEO targets the ten blue links; GEO targets the cited answer. Marketing teams that ignored SEO in 2003 missed a decade of organic traffic. Marketing teams that ignore GEO in 2026 will miss the next decade of AI-mediated discovery.

Agentic AI for marketing

AI agents that take action inside marketing systems. Placing bids, scoring creative, reallocating spend. Not just answering questions.

Agentic AI for marketing means deploying AI systems that take action. Placing bids, scoring creative variants, flagging brand violations, reallocating spend, watching audience segments. Rather than just answering questions for a human. Agents run continuously, integrated with the platforms where decisions actually get made: Amazon Ads, Walmart Connect, Instacart Ads, CRM, brand workflows, creative pipelines. The marketing team supervises the agents; the agents do the trading.

Retail media AI

AI agents that optimise spend, creative and targeting across retailer ad networks like Amazon, Walmart and Instacart.

Retail media AI is the use of AI agents to optimise spend, creative and audience targeting across retailer-owned ad networks. Amazon Ads, Walmart Connect, Instacart Ads, Target Roundel, Kroger Precision Marketing. These networks now represent the third largest digital ad category after Google and Meta, and they reward continuous AI-driven optimisation. The complexity of multi-SKU, multi-retailer coverage makes retail media one of the highest-leverage applications of agentic AI in marketing.

Creative scoring AI

AI that evaluates every creative variant against brand fit, hook strength and predicted CTR before it ships.

Creative scoring AI evaluates every creative variant (copy, image, video) against three dimensions: brand fit, hook strength and predicted CTR. Variants that exceed a promotion threshold ship to live spend; the rest are killed. The result is a continuous, opinionated promotion pipeline rather than a quarterly creative review. Combined with generative pipelines tied to retail media, it produces variants at the pace the platforms reward.

Brand compliance AI

AI agents that check every creative output against brand voice, claims and regulatory standards before it ships.

Brand compliance AI is a layer of specialised agents. Sentiment, intent, brand voice, claims, PII redaction, image safety. That check every piece of creative output before it ships. Each agent reads a market-specific rule set (US, UK, EU, JP). The system catches violations in seconds rather than days, with a full audit trail. Replaces the manual legal-and-brand review cycle that slows enterprise marketing teams down.

Audience segment AI

AI that scores audience cohorts on growth, share and trend in real time, surfacing where spend should move.

Audience segment AI continuously scores audience cohorts on growth, share and trend in real time. Hot segments get more spend; cooling segments get diagnosed before they break. The system answers the question every board asks: where is growth actually coming from? It surfaces the segments driving incremental growth, with the underlying data.

Efficiency monitor AI

AI agents that watch marketing spend across channels continuously and surface waste as it happens.

Efficiency monitor AI watches every marketing channel, every campaign and every retailer continuously. Anomalies surface in seconds rather than in next month's review. The system reallocates spend across channels as soon as the underlying ROAS shifts, so waste is caught and recovered as it happens. Not after the quarter closes.

Anthropic Claude Partner Network

Also known as
Claude partners

A vetted programme of services firms building production systems on Anthropic's Claude foundation models.

The Anthropic Claude Partner Network is a vetted programme of services firms that build production systems using Claude foundation models. Partners get early Claude access, joint engineering support and are recommended by Anthropic for enterprise engagements. 2PT is a partner in the network, using Claude as the foundation-model layer for production agentic systems deployed inside enterprise marketing organisations.

AI engineering firm

A services firm whose deliverable is a production AI system the client owns and operates, not a deck or a SaaS subscription.

An AI engineering firm builds and deploys production AI systems inside a client's stack. The deliverable is live software the client owns after the engagement, not a roadmap, not a license. AI engineering firms typically forward-deploy engineers, price against operational KPIs and specialise vertically (marketing, finance, supply chain). 2PT is an AI engineering firm vertically specialised in marketing, advertising and communications.

Marketing function modernization

The process of re-engineering a marketing organisation around AI systems rather than agency hours.

Marketing function modernization is the process of re-engineering a marketing organisation around AI-driven systems rather than agency hours and SaaS dashboards. The work spans diagnostics, custom deployment, enterprise integration and adoption. Turning a campaign-led function into a system-led one. The marketing team supervises systems; the systems do the trading, scoring and compliance. 2PT modernises marketing functions through embedded AI engineering.

AI deployment services

Services that build, integrate and hand over production AI inside a client's stack.

AI deployment services cover the full lifecycle of getting AI into production inside a client's stack: strategy and diagnostics, custom build, enterprise integration, adoption and transfer. The deliverable is live software, not a recommendation document. 2PT's engagements run on this four-stage model and produce systems the client owns at the end.

Chedder

Also known as
GEO audit · AEO audit · Generative engine audit · AI search audit · LLM citation audit

2PT's complete GEO audit for DTC brands. Live at chedder.2pt.ai. Measures where AI search engines cite a brand and where they send shoppers instead.

Chedder is the productised GEO/AEO audit system built by Two Point Technologies, live at chedder.2pt.ai. It runs the exact questions shoppers ask ChatGPT, Perplexity and Google for a given category, then shows whether the brand shows up in the AI answer, where AI sends shoppers instead, and the specific schema and content fixes required to close each gap. Chedder is built for DTC and consumer brands operating in the generative-search era, and is deployed and customised inside engagements.

Lumen

Also known as
Customer intelligence platform · Multi-tenant customer intelligence · Portfolio intelligence platform · Cohort scoring platform

2PT's central customer brain for a portfolio. Deep per-brand insight, with learning that can be shared with the fund or kept private.

Lumen is the productised customer-intelligence platform built by Two Point Technologies. One central brain, many tenants. Every brand in a portfolio plugs into the same brain and gets the deepest view of their own customer they have ever had, covering cohort behaviour, LTV shape, funnel drop-off, creative response and retention triggers, inside a skin that feels native to their team. The underlying data model is framed differently for marketers, founders and boards, so the same view lands right for each role. On top of that, every brand chooses per experiment whether the learning stays private or joins the portfolio pool. When a shared experiment lands, Lumen matches the audience shape against every other tenant and surfaces the winning play as a suggestion where it is likely to work. Data stays with the brand; only the plays the brand chose to share travel. Sits on top of each brand's commerce, CDP, retail-media and CRM stack with no rip-and-replace.

Cross-brand learning

Also known as
Portfolio learning · Cross-tenant learning · Shared experiment mesh · Symbiotic learning

Opt-in shared learning across a portfolio of brands. Winning experiments a brand chose to share surface as suggested plays in the others where the audience shape matches.

Cross-brand learning is an opt-in shared learning fabric that sits above a portfolio of brands or business units. When a brand runs an experiment and it lands (a cohort test, a price test, a creative test, a funnel change) they choose whether that learning stays private or joins the portfolio pool. When they share, the system matches the audience and behaviour shape against every other tenant and surfaces the winning play as a suggestion in the tenants where it is likely to work. Data never travels; only the plays a brand chose to share travel. The pattern is especially valuable inside venture portfolios, holdcos and multi-brand groups where one operator is paying to learn something a sister brand already proved. 2PT builds cross-brand learning into Lumen deployments.

Conduit

Also known as
Marketing-ops plumbing · Cross-stack alerts · Slack Monday integration

2PT's productised marketing-ops plumbing. Wires Slack, Monday, CRM, retail media and creative pipelines into one stack.

Conduit is the productised marketing-ops integration system built by Two Point Technologies. It links Slack, Monday, the client's CRM, retail-media platforms and creative pipelines into one curated, opinionated workflow stack. Pre-wired flows ship plug-and-play so the marketing team gets an immediate efficiency boost without a six-month integration project. Conduit is how 2PT closes the gap between strategy and execution: the system routes decisions, alerts, briefs and bid changes through the platforms where decisions are actually made.