About Galley
Galley is a culinary resource planning platform transforming how food service organizations manage their operations. Much like ERP systems transformed manufacturing, Galley helps culinary teams structure, organize, and operationalize recipe data so they can run more efficiently and scale with greater precision and consistency.
In an industry historically underserved by technology, Galley gives culinary teams modern tools to manage the data behind their operations while allowing them to focus on what matters most: cooking great food.
The Challenge: Turning Unstructured Recipe Data into Usable Data
For Galley and its customers, one of the biggest barriers to adoption was getting existing culinary data into the platform.
Recipes arrive in countless formats — PDFs, spreadsheets, documents, and other unstructured files — and converting that information into Galley’s structured data model traditionally required significant manual work.
“A big challenge in our business—and for the industry—is onboarding and getting data into our system.”
Benji Koltai
CEO, Galley
Galley had been building toward an AI-enabled future since its founding, but as the company began implementing generative AI, the team needed additional expertise to turn that vision into a production-grade system that could scale.
“We’ve been building toward being AI-ready since we were founded. But I realized that neither I nor my team had the expertise that others had—and that’s why we turned to Tribe.”
Benji Koltai
CEO, Galley
Why Galley Chose Tribe AI
Galley partnered with Tribe AI to bridge the gap between generative AI experimentation and production implementation.
The collaboration began with a rapid design sprint focused on building an initial recipe parser. The early results gave Galley confidence to expand the engagement, ultimately evolving the work from a single use case into a broader AI infrastructure strategy.
“It was a one-stop shop. I needed a designer, a product manager, an AI engineer, a prompt engineer—and I was impressed by the caliber of people in each of those disciplines.”
Benji Koltai
CEO, Galley
Tribe worked alongside Galley across product, design and engineering to take the system from initial validation through production deployment.
Building an AI-Powered Recipe Importer with Claude
Together, Galley and Tribe built an AI-powered Recipe Importer capable of ingesting recipes in a variety of formats and converting them into Galley’s structured data model.
At the center of the system, Claude interprets unstructured recipe content and extracts the information needed to transform it into usable Galley data.
Instead of requiring culinary teams to manually recreate recipes field by field, the system handles the bulk of the parsing, conversion, and normalization automatically, with human review built into the workflow.
What the Claude-Powered System Can Do
Single Recipe Parser
Transforms an individual recipe into structured Galley data with a human-in-the-loop interface for rapid review and onboarding.
Bulk Recipe Parser
Processes large batches of recipes, making high-volume data migrations significantly faster for Galley’s internal teams.
Menu Plan Importer
Transforms unstructured menu plans into Galley’s structured menu-plan format.
Normalization & Deduplication
Cleans and reconciles ingredient data against existing records to create canonical and customer-specific datasets.
How It Works
- Import. Recipes are ingested from a range of unstructured formats, including PDFs and spreadsheets.
- Split. Documents containing multiple recipes are separated into individual recipes for processing.
- Extract. Claude analyzes the unstructured content and extracts key recipe information.
- Convert. The extracted information is mapped into Galley’s internal data schema.
- Reconcile. Ingredient and recipe data is normalized, deduplicated, and reconciled against Galley’s existing data before validation.
Built for Production
This wasn't simply a standalone AI demo. Tribe and Galley built the Recipe Importer to operate within Galley’s production environment and existing product infrastructure.
Tribe also developed a custom end-to-end testing framework using LLM-based judges to validate individual stages of the pipeline, helping Galley evaluate the quality and reliability of outputs before they reached users.
From 10 Minutes to Under a Minute
The impact of the Recipe Importer was immediate.
Before the Claude-powered workflow, entering a recipe into Galley could take up to 10 minutes per recipe. With the Recipe Importer, that process takes less than one minute.
That improvement becomes particularly significant when customers need to migrate hundreds or thousands of existing recipes into Galley.
From a 90-Day Sales Cycle to 29 Days
The impact extended beyond operational efficiency.
The Recipe Importer became a central part of Galley’s sales demonstrations, allowing prospects to see their own recipe transformed into structured Galley data in real time.
“We ask prospects to tell us a recipe they made yesterday. We plug it into the AI, let it do its thing, and then show them that recipe in Galley. It’s mind-blowing for folks still using pencil and paper.”
Benji Koltai
CEO, Galley
After releasing the Recipe Importer in February, Galley saw its average sales cycle fall dramatically.
“Prior to Q1, we had about a 90-day time to close. After releasing the recipe importer in February, we ended Q1 at 29 days.”
Benji Koltai
CEO, Galley
Galley’s Experience Working with Tribe AI
For Galley, Tribe operated as an extension of its internal team, bringing together AI engineering, product, design, and specialized expertise as the initiative expanded.
“By working with folks who are plugged into the cutting edge, we benefited from expertise that we couldn’t match internally. Trying to learn from what’s written online, I’d already be behind the curve. Tribe helped us leap ahead.”
Benji Koltai
CEO, Galley
The initial Recipe Importer also became the foundation for a broader AI strategy inside Galley.
Galley now thinks about AI workflows across two categories: “out-in” agents, which bring external data into Galley, and “in-in” agents, which transform and enrich data already within the platform.
“This project laid the foundation for an entire AI strategy.”
Benji Koltai
CEO, Galley
Claude in Production
The Claude-powered Recipe Importer is now deployed in Galley’s production environment, turning a historically manual onboarding process into an intelligent, scalable workflow.
What started as an effort to simplify recipe import has become part of the foundation for Galley’s broader AI strategy — helping the company move toward a platform where AI can ingest, clean, structure, and ultimately help users act on culinary data.
For Galley’s customers, the immediate impact is much simpler: getting their existing data into Galley no longer needs to be the barrier it once was.