VortexifyAI

What do they actually do

VortexifyAI offers a platform for building task‑specific AI bots for supply‑chain and manufacturing operations. Teams connect existing systems like ERP/MES (e.g., SAP, Oracle) and streaming sources (e.g., Kafka), then build dashboards and Python functions inside the product to give bots the tools they need to analyze issues and suggest or trigger actions VortexifyAI site.

Users create bots with tailored instructions and per‑bot memory, run them in co‑pilot (assistive) or autonomous modes, and schedule or trigger them from real‑time alerts. The platform includes human‑in‑the‑loop approvals, notifications, role‑based access control, SSO, and SOC‑2‑style controls, and it states that model providers aren’t allowed to use customer data for training VortexifyAI site.

The product is presented as live, with demo booking, same‑day onboarding, and free credits after signup. The company is very early stage (YC lists team size 1) and active in YC’s directory VortexifyAI site YC listing.

Who are their target customer(s)

• Manufacturing engineer: Data sits across ERP/MES, logs, and spreadsheets, so finding root causes and fixes is slow. They need a way to connect sources and use dashboards/assistive bots to troubleshoot faster VortexifyAI site YC listing.
• Production planner / scheduler: Forecasts and schedules slip due to siloed data and manual workarounds. They need live data monitoring and optimization that alerts or suggests changes from ERP/MES context VortexifyAI site YC listing.
• Maintenance / reliability engineer: Reactive backlogs grow and it’s hard to predict failures. They need agents to surface likely failures, prioritize work, and tie into maintenance systems so crews focus on the right tasks YC listing VortexifyAI site.
• Plant / operations manager: Wants real‑time visibility and automation but worries about errors and audits. Needs guardrails, approval gates, and security controls before scaling automation VortexifyAI site.
• IT / industrial automation lead: Must integrate ERP/MES, streams, and code securely and auditably. They want faster integration and strict RBAC/SSO/SOC‑2 controls while letting ops teams build useful bots VortexifyAI site YC listing.

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

• First 10: Run high‑touch pilots at a handful of plants (2–6 weeks), with rapid connector setup, free credits, and founder‑led delivery to hit one clear KPI (e.g., downtime or backlog). Use results to create a reference and case study VortexifyAI site YC listing.
• First 50: Standardize the pilot playbook (connectors, 1–2 prebuilt bots, pricing template) and add sales engineers for targeted outbound plus webinars. Sign a few system integrator/ERP‑consulting partners to co‑deliver and feed leads VortexifyAI site YC listing.
• First 100: Launch a template/bot marketplace and self‑serve onboarding for lower‑risk use cases; complete SOC‑2/security packages for enterprise deals. Lean on channel partners and early references; shift from pilots to annual, ROI‑based contracts VortexifyAI site YC listing.

What is the rough total addressable market

Top-down context:

Near‑term, VortexifyAI aligns with the agentic/industrial AI slice, estimated around USD ~5.5B in 2025 with strong growth through 2030 Mordor Intelligence. If it expands into MES/MOM and supply‑chain software, adjacent markets cumulatively reach tens of billions over the next decade MarketsandMarkets Allied Market Research GMI.

Bottom-up calculation:

There are roughly 7.5M factories worldwide; assuming 1–2% are near‑term targets (mid‑to‑large plants with ERP/MES) and an average annual spend of ~$50k–$100k per site on agentic ops bots, the near‑term TAM lands around ~$3.75B–$15B ABI Research.

Assumptions:

• Focus on mid‑to‑large factories with existing ERP/MES (1–2% of global sites)
• Average ACV per site ~$50k–$100k for multiple bots and integrations
• TAM reflects software/agent spend only (does not include broader MES/SCM replacement)

Who are some of their notable competitors

• C3 AI: Enterprise AI applications for manufacturing and supply chain (e.g., predictive maintenance, inventory optimization); competes on prebuilt apps and large‑enterprise credibility.
• Seeq: Advanced analytics for process manufacturing; used for root‑cause analysis, monitoring, and collaboration on time‑series data—overlaps with troubleshooting and optimization use cases.
• Cognite (Cognite Data Fusion): Industrial data platform to unify OT/IT data and build AI apps; relevant where data integration and operational AI sit on top of large, complex asset bases.
• Tulip: No‑code platform for building shop‑floor apps and workflows; alternative for digitizing operations and integrating devices/systems without explicit AI agents.
• Microsoft Dynamics 365 (Copilot for Supply Chain): ERP‑embedded AI assistants for supply‑chain planning and operations; appeals to teams standardized on Microsoft’s stack and tight ERP integration.