— The Techtris blog
Restaurant technology, thought through.
Strategy, systems, and AI for the teams behind restaurant brands. No basics, no hype.
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When AI agents place the order: getting your menu and APIs ready for agentic commerce
AI agents are starting to search, compare, and order for guests. The brands they pick will be the ones whose menus, availability, and order APIs a machine can trust without guessing.
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Build, buy, or compose: owning your ordering stack without building everything
Brands feel stuck between rented ordering templates and costly custom builds. Composing the stack lets you own what differentiates you, buy what does not, and keep every choice reversible.
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Menu as data: the canonical model behind every multi-brand operation
The menu is the most shared object in a restaurant business and the most copied. A canonical menu model turns it into data you publish, not screens you edit channel by channel.
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Stop choosing between marketplaces and first-party. Design a channel portfolio.
Marketplaces and first-party ordering do different jobs. Treat them as a portfolio with explicit roles, pricing rules, and data flows, and the "which one" debate goes away.
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The integration tax: designing a restaurant stack that survives provider changes
Every point-to-point integration charges a recurring tax in maintenance, outages, and lock-in. A shared domain model and a few proven patterns keep the bill small and make provider swaps routine.
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Loyalty after the points era: personalization with first-party data and AI
Points programs have converged into sameness. The next edge is relevance: offers built on first-party data, measured by incrementality, and delivered in an experience the brand owns.
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One platform, many brands: the operating model for restaurant portfolios
Running every concept on its own stack multiplies cost and slows every launch. A portfolio operating model shares the foundations, lets each brand look like itself, and makes governance explicit.
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Throughput is the new UX: designing ordering around kitchen capacity
The ordering screen gets the design attention, but the kitchen decides the experience. Capacity-aware ordering makes honest promises, paces demand by station, and treats quote accuracy as a core metric.
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Where AI actually pays off in restaurant operations, and where it doesn't yet
An AI-native team's honest map of restaurant AI: where it earns its keep today, where it is still premature, and a simple way to rank use cases by value, risk, and data readiness.
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