burnt

What do they actually do

Burnt runs an AI agent that connects to a distributor’s existing ERP and automates order intake. It captures messy orders coming in via email, phone/voicemail, WhatsApp, PDFs, spreadsheets or fax, interprets the items and delivery notes, maps them to the ERP’s product catalog, and creates the sales order—without requiring a system replacement. When details are unclear, the agent asks the customer for clarification and resumes processing once it has the answer (getburnt.ai; YC).

Today it’s used by independent food distributors across categories, with at least one large UK conglomerate in implementation. Public reports say Burnt has processed more than $10M in monthly orders since launch and raised a $3.8M seed round, with the company also sharing high automation rates and big time reductions on order entry as customer-reported outcomes (TechCrunch; PR Newswire; company-reported metrics via FoodNavigator and Fondo).

Who are their target customer(s)

• Independent regional food distributors (meat, seafood, specialty, packaged foods): Most orders arrive over email, phone/WhatsApp, PDFs or fax. Teams spend hours typing, correcting, and mapping shorthand to a legacy ERP, creating delays and errors (getburnt.ai; YC).
• Mid-size distributors on older ERPs across many product lines: They need automation that plugs into the current ERP. Customer-specific shorthand, pack sizes, and catalog mapping break naive rules-based tools, and a rip-and-replace is too risky (getburnt.ai; YC).
• Operations managers for order entry and fulfillment: Their team handles low-value data entry, spins up temps during spikes, and fixes order errors that delay shipments and hurt customer satisfaction (getburnt.ai; FoodNavigator).
• Customer-facing sales reps taking orders over informal channels: They lose time clarifying missing details and re-entering shorthand into the ERP, which slows response times and service quality (getburnt.ai).
• Finance and credit teams (collections, invoicing, credit limits): Reconciliation and collections are manual and slow today; they need help surfacing or acting on routine credit and billing decisions as the product expands beyond order intake (YC; getburnt.ai).

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder-led outbound to a tight set of independent regional distributors; sell short paid pilots that include ERP integration and catalog mapping, then convert pilots into case studies and references.
• First 50: Hire a small sales team to run parallel pilots using the same playbook. Add channel partners (ERP consultants, distributor associations, local wholesalers) for warm introductions and co-selling.
• First 100: Package onboarding/categorization into implementation tiers and a light self-serve path for simpler ERPs. Formalize partners, pricing, SLAs, and referrals so inbound and channel-driven deals supplement direct sales.

What is the rough total addressable market

Top-down context:

U.S. foodservice distributors post about $382B in annual sales—the order flow Burnt’s agent sits on top of if widely adopted (IFDA). Distributor counts are in the tens of thousands in the U.S. under NAICS 4244 (grocery and related product wholesalers) (NAICS).

Bottom-up calculation:

If Burnt serves 10,000–20,000 suitable distributors globally at an average $15k–$60k ARR per account, the software TAM would be roughly $150M–$1.2B at full penetration. Public traction implies a low take rate on order value today (TechCrunch).

Assumptions:

• Targetable global distributor base of 10k–20k after filtering for size, channels, and ERP fit.
• Average contract value of $15k–$60k ARR depending on modules (order intake only vs. multi-agent).
• Full-penetration scenario for TAM; near-term SAM is a subset in initial geographies.

Who are some of their notable competitors

• Conexiom: Document-driven order automation that extracts from emailed POs/invoices and posts to ERPs; strong in manufacturers/distributors with rules-based capture vs. conversational, multi-channel agents.
• Choco (OrderAgent): Food-industry ordering platform whose OrderAgent learns product preferences and can push verified orders into supplier systems; overlaps in food but approaches from a marketplace/ordering product.
• Esker: Enterprise document-capture and order-management software automating PDFs/EDI/email into ERPs; broad, proven scope across industries, less focused on informal channels like calls/WhatsApp.
• Canals.ai: Startup targeting distributors with AI workflows for sales order entry, part-number conversions, and purchasing; competes on ERP connectivity and automation depth in distributor workflows.
• Endeavor.ai: AI order-entry agents that capture orders from emails, PDFs, and spreadsheets and place them into ERPs; direct competitor on intake automation, with differences in channel coverage and industry focus.