Panora

What do they actually do

Panora is a SaaS tool that reads purchase orders and RFQs sent to a company’s email inbox, converts them into clean structured data, matches the items against the company’s product catalog, and creates validated purchase orders directly in the ERP. Customers route PO/RFQ emails to Panora, review any flagged exceptions (duplicates, mismatches, missing fields), and let the system post clean orders in real time to their ERP with a human‑in‑the‑loop option when needed (getpanora.com). The product is live with a web app and demo flow, and the company is a YC S24 startup (app.getpanora.com, YC profile).

Beyond extraction and posting, Panora keeps developer‑facing integration options via an SDK/API so teams can embed or extend the workflow programmatically (npm @panora/sdk). The company previously offered an open‑source integration toolkit and has since pivoted to this vertical SaaS product, as noted in their GitHub repo which now points to the commercial offering (GitHub panoratech/Panora).

On the roadmap, they plan to surface operational signals (e.g., inventory, pricing, and churn indicators) and add “AI Actions” to follow up automatically, alongside expanded order automation features like rerouting when stock is low and a returns watchdog (getpanora.com).

Who are their target customer(s)

• Order‑entry clerks at distributors and wholesalers: They spend hours rekeying emailed POs, fixing typos, and handling exceptions, which leads to slow order entry and errors that ripple downstream (Panora product).
• Purchasing or operations managers: Manual updates and mismatched SKUs cause late or incorrect ERP data, leading to stockouts, wrong purchases, and slower supplier responses (Panora: item matching & ERP posting).
• ERP administrators and internal IT teams: They maintain brittle, custom connectors and constantly clean up inconsistent PO data before it hits the ERP; they prefer reliable APIs/SDKs and packaged logic (Panora SDK/API presence, Panora GitHub history).
• Sales or account managers: Signals like partial orders, repeat RFQs, or pricing issues are buried in inboxes; there’s no automated way to detect and follow up quickly (Panora: signals & Sales AI Agents).
• Warehouse and fulfillment leads: Duplicate shipments, mismatched items, and unmanaged returns increase labor and shipping costs and drive customer complaints (Panora: duplicate detection & returns watchdog).

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

• First 10: Founder‑led pilots via warm intros and targeted outreach; run hands‑on, low‑cost pilots that connect to the customer’s ERP and catalog, focusing on measured time saved and error reduction to create references (getpanora.com).
• First 50: Hire 1–2 reps to run repeatable outbound to order‑entry, ops, and ERP admins; productize top ERP connectors and onboarding steps; support with 2 case studies and an ROI template; partner with ERP consultants (GitHub panoratech).
• First 100: List connectors in ERP marketplaces and recruit VAR/ERP consultancy partners; add a self‑serve trial with an ROI dashboard for smaller distributors; drive referrals and a focused content/webinar playbook (getpanora.com).

What is the rough total addressable market

Top-down context:

In the U.S., wholesale trade (NAICS 42) includes roughly 633k private‑industry establishments and over $11.3T in annual merchant wholesaler sales in 2022, indicating a large base of distributors handling orders and ERP workflows (BLS NAICS 42 IAG, Census AWTS).

Bottom-up calculation:

If Panora targets the order‑entry‑heavy segment of wholesale distributors and manufacturers that still process POs from email, assume ~20% of ~634k U.S. wholesale establishments are in‑scope (~127k) and an average ARPA of ~$10k–$20k for inbox→ERP automation and exception handling, implying a U.S. TAM of ~$1.3B–$2.5B. Global opportunities would expand this further.

Assumptions:

• Only a subset of wholesale establishments fit Panora’s email‑PO, ERP‑connected ICP (~20%).
• Average contract size of $10k–$20k ARR per customer for PO extraction, catalog matching, and ERP posting.
• TAM scoped to U.S. wholesale/manufacturing workflows; global and adjacent verticals not included.

Who are some of their notable competitors

• Rossum: Enterprise IDP that extracts data from emails/PDFs (orders, invoices), validates against master data, and connects to ERPs. Overlaps on PO extraction and validation but is positioned as a broad document platform, not distributor‑specific catalog matching (platform, order management).
• Esker: Order‑to‑cash and source‑to‑pay suite that ingests orders from email/EDI/PDF with rules and multi‑ERP integrations. Competes on breadth for larger enterprises; Panora focuses on narrow inbox→ERP PO workflows for distributors (order management, all ERPs).
• Tradeshift: Procure‑to‑pay and supplier network with PO/invoice digitization, matching, and collaboration. Strong where buyers want network effects and compliance; Panora targets mailbox‑driven distributor processes (P2P, AP/PO).
• Parseur: No‑code email/PDF parser that can extract PO line items and forward JSON. Overlaps on parsing, but leaves catalog matching, de‑duplication, and ERP write logic to the buyer’s stack (PO automation, webhook export).
• UiPath (RPA / Document Understanding): RPA and document understanding used to build custom bots that read POs and drive ERPs. Highly flexible but heavier to build and maintain versus a packaged inbox→ERP assistant (email automation, PO ML package).