AgentMesh.help
Freemium
Developers integrating AI agents into task workflows
CortexaPro AI
FreemiumAPIAgentic
Six systems, six consoles, zero shared context — and every cross-team workflow dies in someone's inbox waiting for a manual handoff. CortexaPro is built to sit on top of that stack and replace the handoffs with agents that actually execute.
$5/mo - $95/mo · Free tier: 50 credits/month, 1 team member, Cortexa Companion and Cortexa Studio only, 7 day log retention, Email support (48hr) · Checked Jul 1, 2026
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Screenshots 1
Summary
The platform covers two distinct audiences: enterprise teams wiring agents into CRM, ERP, HR, and ITSM pipelines, and individual users who want multi-model chat plus life tools in a single interface. The enterprise side offers an agent builder with custom logic, memory, and decision layers, plus role-based access controls and audit logs — the table stakes for any org that will face a compliance review. The Cortexa Launchpad marketplace lets you hand a screenshot or API spec to a purpose-built agent and get production-ready code or UI back. The credit-metering model means costs are trackable, but teams running high-volume pipelines will hit the ceiling of a credit allocation faster than the pricing page suggests.
Bottom line: Bet on CortexaPro when you need to connect disconnected enterprise systems under a single audit-ready layer — but plan for a rearchitect if your pipeline volume outpaces what the credit model can absorb without the economics breaking.
Pricing Plans
Usage-BasedLast verified 4 months ago- Price
- $5/mo - $95/mo
- Free Tier
- 50 credits/month, 1 team member, Cortexa Companion and Cortexa Studio only, 7 day log retention, Email support (48hr)
Free
Free
Explore AI capabilities
- 50 credits/month
- 1 team member
- Cortexa Companion
- Cortexa Studio
- Email support (48hr)
- 7 day log retention
Starter
$5per month
Get started with AI
- 500 credits/month
- Unlimited team members
- Cortexa Companion
- Cortexa Launchpad
- Cortexa Academy
- Cortexa Studio
- Email support (36hr)
- Credit top-up available
Growth
$15per month
Scale your daily AI usage
- 2,500 credits/month
- Unlimited team members
- All AI products
- Email support (24hr)
- Credit top-up available
- 90 day log retention
Pro
$45per month
Run advanced AI workflows
- 10,000 credits/month
- Unlimited team members
- All AI products
- Email support (12hr)
- Credit top-up available
- 180 day log retention
Scale
$95per month
Power business-wide AI operations
- 30,000 credits/month
- Unlimited team members
- All AI products
- Dedicated support
- Credit top-up available
- 365 day log retention
Enterprise
Custom
Custom AI infrastructure & deployment
- Unlimited credits
- Unlimited team members
- All AI products
- Dedicated support
- Credit top-up available
- Unlimited log retention
View full pricing on cortexapro.ai →
Pricing may have changed since last verified. Check the official site for current plans.
Find your fit
Before you choose CortexaPro AI
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Pros
- Agents connect to existing CRM, ERP, ITSM, and HR systems without replacing them, so teams avoid a migration project just to get automation running.
- Role-based access controls with audit logs and execution tracking on every request, which means compliance reviews have a paper trail rather than a gap where the AI ran.
- Purpose-built Launchpad agents with scoped inputs and outputs — Screenshot→Component, API Spec→Backend — so developers get production-ready code without writing prompts from scratch each time.
- Multi-region deployment across four regions with localized compliance handling, so organizations operating across regulatory jurisdictions do not have to build a separate data-routing layer.
- Credit metering on all agent runs gives finance and engineering a single number to audit, avoiding the surprise overages that come with per-seat or unlimited-call models.
Cons
- No self-hosted option exists — the platform is cloud-only. Any org under a hard data-residency or air-gap requirement hits this wall before a single agent is built, and those teams move to a self-hostable alternative like Dify or n8n rather than negotiate a carve-out.
- Credit-metered billing means high-volume production pipelines — document generation or approval workflows running at enterprise scale — exhaust credit allocations before the billing cycle ends. Teams running batch workloads report needing paid upgrades to maintain throughput, which changes the economics that the free tier implied.
- The platform bundles enterprise orchestration and consumer life tools under one product surface. Engineering leads evaluating the agent builder for production deployments have no clean way to separate the roadmap priorities of a B2B workflow platform from those of a consumer chat app — product direction risk that a pure-play enterprise tool does not carry.
About
- Platforms
- Web (SaaS)
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- June 18, 2026
Best For
Who it's for
- Enterprise teams needing agentic automation across disconnected systems
- Developers building and scaling custom AI workflows
- Organizations requiring audit-ready, compliant AI orchestration
- Users seeking credit-metered agent marketplace access
What it does well
- Automate cross-system workflows in CRM, HR, and finance
- Generate production-ready code, UI components, or architecture from inputs
- Orchestrate document generation, approvals, and reporting pipelines
- Provide adaptive practice for IT certifications and global exams
- Multi-model chat and creative tools in one interface
Integrations
Frequently Asked Questions
- Is CortexaPro AI free?
- CortexaPro AI offers a free option alongside paid upgrades. Pricing: $5/mo - $95/mo. Check the current allowances and terms before choosing a plan.
- Does CortexaPro AI have an API?
- Yes. CortexaPro AI exposes a developer API. See the official documentation at https://cortexapro.ai for details.
- What platforms does CortexaPro AI support?
- CortexaPro AI is available on: Web (SaaS).
Curated lists that include this category
CortexaPro is a cloud-only agentic AI platform designed to orchestrate work across enterprise systems — CRM, ERP, HRMS, ITSM, and finance APIs — without replacing them. The core workflow runs through its Studio environment: you design an agent with structured inputs, memory, and decision logic; connect it to data sources and event triggers; then deploy it into a production pipeline with execution metrics and credit metering tracking every run. The vendor describes this as a four-stage arc — disconnected systems today, hidden manual costs, CortexaPro stepping in, proactive zero-touch outcomes — and the product is built around that promise of replacing reactive operations with automated pipelines.
The differentiating layer is the Cortexa Launchpad, a marketplace of purpose-built agents where each agent has a single, scoped job: Screenshot→Component, API Spec→Backend, Schema→Admin Panel, Legacy→Modern. You hand the agent an input and get a production-ready deliverable. This is meaningfully different from a general-purpose code assistant — the agents are pre-scoped so you are not prompt-engineering your way to an output; the job is already defined.
The platform fits teams that need audit-ready orchestration across disconnected systems and want to move without a rip-and-replace. Role-based access, department-level isolation, execution tracking, and multi-region deployment across US, UK, India, and MENA are all described on the product page. Where it breaks: the platform is not self-hosted, which closes the door for any org with a hard data-residency requirement that a multi-region SaaS deployment does not satisfy. Credit metering gives visibility into costs but also introduces a hard ceiling — high-throughput pipelines will exhaust allocations and require paid upgrades to keep running.
The platform also bundles a consumer-facing layer — multi-model chat across GPT, Claude, and Gemini, AI image generation, and 30+ life-tool categories — under the same Cortexa brand. For enterprise buyers evaluating the platform on workflow automation, this dual positioning can create confusion about where the product’s engineering investment actually sits.
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