Adoption
Choosing EgentWrX is not buying a product. It is choosing a complete AI solution that actually lands
EgentWrX comes with the full feature set, priced by number of users (50 or more recommended). There is really only one decision to make: whether your data sits in the cloud or in your own environment.
Every enterprise-grade core capability, in one EgentWrX
We put weight on a step-by-step rollout and on features that actually land. EgentWrX does not sell its management capabilities separately, and does not strip out anything an enterprise needs. Access control, auditing and model switching are always included.
Enterprise · full feature set
The most complete AI agent platform available
- Multiple models, organization-level long-term memory, knowledge bases
- Layered RBAC and auditing across organization, department, role and data
- Agent-to-agent workflows across departments, one-click skill generation
- AD and SSO integration, MCP connections to internal systems
- Cloud models or your own on-premises models
- Edge computing module (EgentWrX EDGE), distributed inference across devices
Two deployment options, for different rollout scales and speeds
Cloud and on-premises carry the same core features. Depending on your internal data control policy, you can deploy in the cloud, in your own data centre, or on an AWS private cloud. The two modes differ considerably in early rollout speed and in how data is governed; for larger enterprises, and those with stricter ISO requirements, we suggest on-premises (including AWS private cloud) as the primary choice, so that data governance requirements are met.
Fastest to launch
We host it. Nothing to build, nothing to maintain. Shortest path from decision to company-wide use, and the lowest upfront cost.
- No build, live on activation
- Automatic updates, operations on us
- Rollout moves quickly, suits fast expansion
Data sovereignty
Deployed in your own data centre or private cloud, with data staying inside the company. Necessary for sensitive data and regulated industries.
- Data stays inside, and in country
- Meets regulation, protects trade secrets (manufacturing, finance, government)
- You own governance and the machines
Cost structure
Software platform licence, compute, training and consulting, plus additional services.
Software licence
Platform licence priced by number of users, including every feature and all updates.
Per userAnnual licence
Compute usage
Model inference usage, tied to what you actually run. Connecting your own on-premises models can bring this part close to zero.
Per usageMuch lower with your own models
Training and consulting
Consulting and workshops during rollout. Project-based, and it declines each year as capability transfers to your team.
ProjectHeaviest at rollout, then falls
Additional services
On-premises setup, systems integration, custom development and extended support. Not everyone needs these; scoped and quoted separately.
On requestOptional
How EgentWrX differs from other enterprise AI tools
Personal AI tools make one person faster. An enterprise rollout also has to govern data, permissions and workflows that cross departments.
- Where your data lives
- Run it in the cloud, or deploy it in your own data centre or private cloud when regulations or trade secrets rule out the public cloud.
- How permissions are layered
- Administrators layer access by department, role, AI Agent and data, controlling who can use what and see what, in line with least-privilege and audit requirements.
- How AI Agents hand off across departments
- Real work is a relay across departments, such as sales to scheduling to purchasing to quality assurance. AI Agents hand work to each other and close the gaps that single-point tools leave open.
How to start evaluating
A dedicated contact works through your requirements with you, then gives an initial analysis and recommendation based on user scale, deployment mode, rollout scope and, most importantly, the results you expect.
Understand the need
Industry, number of departments, expected users, and the process you most want solved first.
About 30 minutes
Recommend an architecture
Based on data sensitivity and compliance, we suggest SaaS, on-premises or hybrid, and assess whether EgentWrX EDGE applies.
With the trade-offs laid out
Scope and quote
Confirm rollout scope and consulting effort, then provide a full quote and schedule.
Each cost item listed separately
Leave your contact details and a consultant will be in touch shortly to work out a suitable starting scope and deployment mode with you.
Frequently asked questions
The questions that come up most often during evaluation. The notes below describe the general case; actual terms depend on the scope of adoption.
- Why do you recommend 50 users or more?
- In our experience, the return on an enterprise AI rollout depends on how many complete workflows the AI takes over, not on how many people use AI. When only a few colleagues are proficient, overall delivery speed and quality are still held back by the slowest step. EgentWrX is built around Agents handing work to one another along the division of responsibility, processing rules and checkpoints of a workflow; where coverage is incomplete the relay breaks at the step no one picks up, and the benefit stays at a single point. Below a certain number of users, complete coverage of a workflow is difficult to achieve.
- Which costs are one-off and which recur annually?
- The main annual cost is the platform licence, priced by number of users, with all functionality and version updates included. Compute is charged on actual inference usage. The one-off cost is environment setup for on-premises or hybrid deployment, covering system installation, the knowledge base and RAG architecture, and external service integration. Consulting and workshops during adoption are charged by the hour; we recommend drawing on the full adoption service to bring AI Agents into everyday work step by step, and as that capability takes root inside the company the consultants withdraw in stages. Custom development and system integration are quoted separately according to actual scope.
- How long does adoption take, and what does the company need to invest?
- Adoption proceeds in three stages: consultant-built, jointly built, then company-built. The actual timeline depends on scope and level of investment. Investment on the company side runs in two directions: management sets policy and targets from the top down, while each function works bottom up to map its tasks and bring them into AI one by one, with front-line staff and middle managers driving the middle stretch together. The goal is at least one seed member per department, the exact number depending on the size and working pattern of the department, able to design, build and maintain Agents independently so the capability stays inside the organisation.
- Beyond where the data sits, how do cloud and on-premises differ?
- The cloud edition is managed by us, with no setup and no maintenance for the company; it is the shortest path from decision to company-wide rollout and the lowest up-front commitment. On-premises and hybrid deployment require a one-off environment setup, with time and cost accounted for separately, and typically suit companies under strict information-security rules, high regulatory requirements, or larger organisations. Core functionality is identical across both; the differences lie in who builds it, how quickly it goes live, and where the boundary of data control sits.
- We would like to start with a small scope. Is that possible?
- Yes, and we usually suggest starting with one department or one workflow. Leave your contact details and a consultant will be in touch shortly to work out a suitable starting scope and deployment mode based on your industry, departments and the workflows you want to address first.
Where to go next
Want every employee to have their own AI teammate?
A consultant will be in touch shortly.