Sold by: Kore.ai
Deployed on AWS
AI for Process is an AI Agent platform designed to automate knowledge-intensive business processes. By combining deep domain AI agents with robust integration, it streamlines operations, reduces human dependency, and boosts compliance and efficiency. It features Multi-Agent Process Automation for handling complex decisions using structured and unstructured data, and Process-Specific AI Orchestration for customizable workflows aligned with business goals. Its Human-in-the-Loop Framework enables human intervention at key decision points. With Enterprise Integrations, it connects systems via standardized data exchange. Pre-configured templates accelerate setup, while built-in Governance & Compliance ensures transparency and industry-aligned control.
4.6
Overview
AI for Process is a powerful agentic AI platform purpose-built for automating knowledge-intensive tasks across business processes. Designed to streamline complex workflows, AI for Process enables organizations to operate more intelligently, consistently, and efficiently by leveraging the deep domain expertise of specialized AI agents. These agents are equipped to handle nuanced decision-making, integrate seamlessly across systems, and uphold regulatory compliance, all while reducing the need for constant human intervention.
At the core of the platform is Multi-Agent Process Automation, where AI agents apply specialized reasoning to make informed decisions, extract insights from both structured and unstructured data, and execute multi-step workflows while ensuring compliance with business rules. This is particularly valuable in industries where accuracy, regulatory alignment, and operational efficiency are non-negotiable. Process-Specific AI Orchestration enables businesses to customize workflows aligned to their unique objectives. These AI agents act in coordination using triggers, approvals, and contextual understanding to optimize outcomes across departments and teams. With contextual awareness, agentic AI applications ensure alignment between automation and business intent.
The platform incorporates a Human-in-the-Loop Framework to ensure critical decisions still benefit from human expertise. With configurable handoff protocols between AI agents and human experts, it ensures that when needed, AI defers to human judgment with the right context, preserving continuity and confidence in decision-making processes.
Governance & Compliance is built into the foundation of AI for Process. AI for Process ensures that all automation activities are transparent, auditable, and compliant with industry-specific requirements. Built-in verification mechanisms, robust process logging, and business rule enforcement make it easier to meet regulatory standards while maintaining operational excellence.
Highlights
- Multi-agent Orchestration: AI agents that handle knowledge-intensive tasks, applying specialized reasoning to make decisions, extract insights from structured and unstructured data, and execute multi-step workflows while maintaining business rule compliance.
- Process-Specific AI Orchestration: AI agents designed for specific business processes, orchestrating their actions through customizable workflows with appropriate triggers, approvals, and contextual awareness to ensure optimal outcomes in line with business objectives.
- Accelerate Process Automation with Templates: Seamlessly integrate human expertise at critical decision points with configurable handoff protocols between AI systems and human experts, providing appropriate context for decisions while maintaining process continuity.
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
AI for Process Enterprise Support | AI for Process Enterprise Support | $40,000.00 |
AI for Process Non Production Cloud Environment | AI for Process Non Production Cloud Environment | $40,000.00 |
AI for Process AI Agents Enterprise | AI for Process AI Agents Enterprise per AI Agent per year | $10,000.00 |
Dimension | Description | Cost/unit |
|---|---|---|
AI for Process AI Agent Runs Enterprise | AI for Process AI Agent Runs Enterprise - Per Agent Run (API Call) | $0.02 |
1000 GPU Hardware Model Credits | AI for Service - AI GPU Hardware Credits | $1,500.00 |
Dimensions summary
You buy AI for Process under a contract across five separate dimensions. Two set your base capacity: AI Agents Enterprise is priced per AI agent per year, and AI Agent Runs Enterprise is priced per agent run, meaning each API call. GPU Hardware Model Credits come in 1000-unit blocks to cover model compute usage. A Non Production Cloud Environment gives you a separate space for testing before production. Enterprise Support is a standalone add-on. You combine these units to match your agent count, expected run volume, compute needs, and support level.
Top-of-mind questions for buyers
An AI Agent Run is billed per agent run, which the pricing table defines as one API call. Each time an agent executes through the runtime engine counts as a separate run. This meters actual usage, so your run charges scale with how often agents are invoked across your workflows.
AI Agents Enterprise bills per agent per year, so it scales with how many agents you deploy. AI Agent Runs bill per API call, scaling with invocation volume. High-traffic agents push run charges up fastest. GPU Hardware Model Credits add compute cost separately. All charges bill independently and combine on one contract.
The GPU Hardware Model Credits come in 1000-unit blocks and cover model compute usage on GPU hardware. Agents that reason, run evaluations, and search knowledge draw on this compute. You buy these blocks separately from your agent and run capacity to match expected model workload.
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AI for Process is an AI Agent platform designed to automate knowledge-intensive business processes. By combining deep domain AI agents with robust integration, it streamlines operations, reduces human dependency, and boosts compliance and efficiency. It features Multi-Agent Process Automation for handling complex decisions using structured/unstructured data, and Process-Specific AI Orchestration for customizable workflows aligned with business goals. Its Human-in-the-Loop Framework enables human intervention at key decision points. With Enterprise Integrations, it connects systems via standardized data exchange. Pre-configured templates accelerate setup, while built-in Governance & Compliance ensures transparency and industry-aligned control. AI for Process empowers enterprises to scale automation with confidence, agility, and regulatory assurance.
Kore AI for Process is an AI-native process automation solution built to automate complex, knowledge-intensive workflows.. It enables business users and developers to orchestrate dynamic, real-world processes with simplicity, AI governance, and scale. Co-existing with existing robotic process automation (RPA) and business process automation (BPM) systems, AI for Process delivers higher automation coverage, faster efficiency, and productivity, without costly rip-and-replace
Processing.AI is Accenture’s Intelligent Document Processing (IDP) solution that uses AI/ML models, OCR, and generative AI to automate extraction, classification, and analysis of structured and unstructured data from documents and images. It improves operational efficiency, ensures compliance, and scales to handle high-volume workflows on AWS, supporting formats like PDFs, images, and text files.
An 8- to 18-week modular program designed for industry specific application and successful realization of business value powered by GenAI and Agentic Solutions on AWS.
Customer reviews
Wissam Ezzeddine
Low-code AI agents have transformed our workflow and training efficiency
Reviewed on Aug 16, 2026
Review provided by PeerSpot
What is our primary use case?
Kore.ai is designed to create AI chatbots for agents working with clients, integrating agents for their main duties.
I completed a personal project using Kore.ai to build an agent for university admissions that handled FAQs and provided answers with generative AI. The project also had knowledge AI integrated and took approximately one month to complete.
Our team worked on assignments for training purposes, including a project for a flight attendant training program, and another project for a client in Dubai. The Dubai project involved creating agents for various duties within the system that could take calls with clients.
What is most valuable?
One of the best features Kore.ai offers is low-code development. Another valuable feature is the integration of different LLMs by simply integrating the API, which is extremely helpful. Different types of apps can be made using Kore.ai, including knowledge-based apps, AI agents, and contact center AI.
The low-code development feature is particularly helpful because there is no need for writing code. There are many blocks that can be arranged together with the logic that anyone wants. What I appreciate most about it is that it integrates easily and can be tested more quickly than the traditional method involving writing code.
The testing process with Kore.ai is straightforward and easy, with minimal rework and repetition.
Kore.ai is going to be a breakthrough for our organization. However, due to market conditions, we did not have many clients interested in working with Kore.ai. The platform has impacted our organization by enabling us to dive into the AI world, specifically regarding agents and chatbots.
My team has noticed improvements in workflow and efficiency while implementing their own chatbots and AI agents.
What needs improvement?
Kore.ai could be improved by offering more in-depth trainings and assignments with the platform itself so that anyone could learn how to use it better.
We sometimes faced challenges with the integration process due to a lack of in-depth knowledge in the documentation. Reading through the documentation carefully helped us resolve any issues.
I assigned a rating of eight because there are sometimes bugs or issues when trying to switch from one app to another, leading to some lagging, which might be related to the GUI itself.
For how long have I used the solution?
I have been using Kore.ai for about three to four months.
What do I think about the stability of the solution?
Kore.ai's accuracy and reliability depend on how we train it and what information we input. Based on our inputs, it is very accurate and reliable, especially for knowledge apps that provide search results and references.
What do I think about the scalability of the solution?
The question about performance under heavy workloads is not applicable for us since we have not deployed Kore.ai fully with clients. We have only tested it with a small team.
How are customer service and support?
The support and documentation for Kore.ai are good as they are, with everything someone needs being clearly available. The technical support team is also very helpful.
Which solution did I use previously and why did I switch?
Kore.ai is outstanding compared to other AI agent platforms such as Copilot Studio due to the centralized nature and integration of different apps within a single platform.
How was the initial setup?
Onboarding Kore.ai was managed by our team lead, who introduced it to us through instructor-led training that involved assignments and recordings, which made the process smooth.
Which other solutions did I evaluate?
My advice for others looking into using Kore.ai is to first introduce themselves to the platform through the academy, engaging in instructor-led trainings, completing assignments, and testing things out for themselves.
What other advice do I have?
The learning curve for Kore.ai took some time because the trainings are scheduled differently, making it hard to incorporate everything quickly. However, the learning process was smooth during the instructor-led trainings.
Before concluding, I think it is important to note how much learning someone needs to achieve a senior position regarding Kore.ai and the experiences that come along with it.
I gave this review a rating of eight out of ten.
Telecommunications
Straightforward IVR Workflow Design, Though Still Room to Grow
Reviewed on Aug 06, 2026
Review provided by G2
What do you like best about the product?
Kore.AI is currently being used by a few of our clients. They mainly use it because it makes IVR workflow design easier and more straightforward.
What do you dislike about the product?
There was no support from the Kore.AI team for certifications on earlier Kore.AI versions, so we had to train our freshers ourselves because the client was still using an older version in production.
What problems is the product solving and how is that benefiting you?
It makes it much easier to implement complex workflows.
Information Technology and Services
Kore.AI’s Flexible Low-Code Platform for Scalable, Enterprise-Grade Chatbots
Reviewed on Aug 04, 2026
Review provided by G2
What do you like best about the product?
What I like best about Kore.AI is its flexibility. The low-code platform makes it easy to build and deploy enterprise-grade chatbots quickly, while still providing the ability to implement complex business logic through custom code, APIs, and integrations. Its omnichannel support, strong NLP/LLM capabilities, and enterprise-ready features make it an excellent platform for developing scalable conversational AI solutions.
What do you dislike about the product?
The main drawbacks are the learning curve for advanced features, limited debugging visibility in complex bot flows, and occasional inconsistencies in AI/Search AI responses that require additional tuning. Improved documentation and debugging tools would make development much smoother.
What problems is the product solving and how is that benefiting you?
Kore.AI helps solve the challenge of building and managing enterprise conversational AI by providing a single platform for chatbot development, AI orchestration, integrations, and omnichannel deployment. It reduces development time through reusable components, low-code tools, and built-in integrations while still allowing custom development when needed. This has enabled us to deliver production-ready chatbots faster, automate customer interactions, integrate with enterprise systems, and focus more on improving user experience rather than building infrastructure from scratch.
Banking
Wide Variety of Connectors That Just Works
Reviewed on Aug 03, 2026
Review provided by G2
What do you like best about the product?
The wide variety of connectors available.
What do you dislike about the product?
Sometimes the platform seems like it's lagging, which impacts the pace of development.
What problems is the product solving and how is that benefiting you?
I would say mostly banking, making it easier for customer with their day to day needs.
Sushil Kumar S.
Exceptional Support and Easy Setup with Kore.AI
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
I find Kore.AI's support very helpful; whenever we get stuck, they are ready to assist quickly. I've worked on many chatbots, and I appreciate how straightforward the initial setup of Kore.AI was for me.
What do you dislike about the product?
I feel like there could be improvements in the inbound and outbound scenario where instances need to select all the parameters like chatbots. It would be helpful if they could add some prompting steps based on current standards. Also, I'm looking for faster resolution for user issues.
What problems is the product solving and how is that benefiting you?
I use Kore.AI to resolve HR and IT issues without manual portal tasks, and it helps me quickly address FAQs based on queries.