Services
From the right opportunity to reliable operation
Four service groups cover the whole path: deciding what is worth doing, building it, helping people use it well, and keeping it working. Each one is described by the outcome it produces, not by the technology involved.
Every engagement starts with a short AI Opportunity Call at no cost. Paid work usually begins with an AI Opportunity Assessment; scope and commercial terms follow once fit is established.
AI Opportunity Assessment
Find the Right Opportunity
Which workflow is worth changing first, and is it worth changing at all?
Business situation
AI looks promising in several parts of the business, but nothing is obviously first. Time is lost in places nobody has measured, every candidate workflow touches two or three systems, and choosing wrong spends budget on something the organization never adopts.
What changes
A short list you can defend: the workflows worth investing in, the ones to leave alone for now, and a recommended first pilot with the reasoning written down so leaders can explain the decision to each other.
What the engagement may include
- Interviews with the people who do the work and the people accountable for the result
- A review of how each candidate workflow runs today, including the manual steps and workarounds
- An inventory of the systems, data sources, and approvals the workflow depends on
- A security and access review of what each candidate workflow would need to reach
- A feasibility analysis, comparing candidates against value, complexity, and risk
What you receive
- A prioritized set of opportunities, each with the value, complexity, and risk reasoning behind its position
- A recommended pilot workflow with success criteria that can be observed rather than asserted
- A written roadmap covering dependencies, approval requirements, and a sensible order of work
- A statement of what was examined, what was assumed, and what remains unknown
What stays with you
- Access to the people who do the work, not only to management
- Accurate information about systems, data, and approvals, including the unglamorous parts
- A named decision-maker who can confirm priority and scope
AI Workflow Pilot · AI Implementation
Build and Integrate
How does the chosen workflow get built and connected to the systems already in use?
Business situation
The workflow is agreed and the value is clear, but the work still moves between systems by hand. Existing AI subscriptions sit beside the business data instead of inside it, so people copy, retype, and re-check rather than decide.
What changes
Less repetitive cross-system handling, approved information that is easier to find and use, and AI-assisted steps that run inside the permissions and systems already in place—with a person still accountable for anything that leaves the team.
What the engagement may include
- Human-reviewed drafting, classification, summarization, retrieval, and record actions
- Connection to existing systems through whichever method fits: an application programming interface, an automation platform, a webhook, a business application plugin, or a custom component
- A permission-aware assistant that answers from approved internal knowledge
- A pilot that runs on one workflow before anything broader is attempted
What you receive
- One workflow running against real work, with success criteria agreed before implementation starts
- Implementation documentation covering what the workflow does, which systems it touches, and who owns it
- A tested rollback path for every action the workflow can take
- Handover to the people who own and operate the workflow day to day
What stays with you
- A process owner who can make decisions during the build
- A safe way to test—synthetic records or a non-production path—whenever the workflow touches real records
- Timely review of outputs while the pilot is being evaluated
AI Adoption
Adopt AI Safely
How do people use these tools well and stay inside the rules?
Business situation
Tools are already in use across the organization, and each person is making individual decisions about what to paste in, what to trust, and when to double-check. If a policy exists, it was written for a different kind of software.
What changes
People know which tool suits which work, what may and may not go into it, and who approves a result that leaves the team. Adoption is measured against the work being done rather than the number of licenses purchased.
What the engagement may include
- Training built around the roles, data, and approved workflows people actually have
- A usage policy written for the tools in use, in language staff can follow
- Selection support for tools that meet the organization’s data-handling requirements
- Safe-use practices for prompting, reviewing output, and handling untrusted content
- A repeatable way to identify the next workflow and to measure whether the change stuck
What you receive
- A written usage policy tied to real roles, data, and approved workflows
- Role-based training with reference material staff can return to
- A practical measure of whether the work changed, using signals the organization already has
- Internal procedures someone inside the organization can repeat without EverythingAI present
What stays with you
- Participation from the roles being trained, not only from leadership
- Agreement on who owns the policy after handover
- Willingness to change a process, not only to add a tool
Ongoing AI Operations
Operate and Improve
Who keeps it reliable, and who notices when it stops being reliable?
Business situation
A workflow is running and useful. Something still has to watch it, answer employee questions, respond when a provider changes a model or an interface, and decide what to improve next.
What changes
The workflow stays reliable and supported after launch. Cost, access, and output quality are reviewed on a schedule instead of after an incident, and improvements are chosen from evidence rather than enthusiasm.
What the engagement may include
- Monitoring and error alerting for the workflow and the systems it depends on
- Usage and cost review, including where a provider change affects either one
- Access review to confirm permissions still match what the work requires
- Model and interface updates when a provider changes something underneath the workflow
- Workflow improvement, employee support, and a periodic strategy review
What you receive
- An agreed alerting and support path, including who inside the organization is contacted first
- A recurring review of usage, cost, and access, with findings recorded
- Documented changes whenever a model, interface, or workflow is updated
- A periodic review of what to build, change, or retire next
What stays with you
- A named internal contact for escalations and decisions
- Prompt reporting of failures or behavior that looks wrong
- An approved change process for anything that touches production work
The free call and the paid Assessment are different conversations
At no cost
AI Opportunity Call
A short fit conversation. It is not a shortened assessment, and no analysis is produced.
- Purpose
- Decide whether EverythingAI and the problem you have are a good fit for each other.
- Time
- 20–30 minutes, arranged at a time that suits you.
- Cost
- At no cost, with no obligation to continue.
- You leave with
- A direct answer about fit and an honest next step—including “not yet” when that is the correct answer.
- It is not
- A written assessment, a prioritized roadmap, or an analysis of your systems, data, and workflows.
Paid engagement
AI Opportunity Assessment
Structured, documented work that ends in a decision you can act on and a plan you can follow.
- Purpose
- Examine the workflows, systems, value, feasibility, and risk, then recommend a workflow worth building first.
- Scope
- Agreed in writing before work starts, based on what the Opportunity Call established.
- Cost
- A paid engagement. Scope, schedule, and commercial terms are agreed in writing before work starts.
- You leave with
- Prioritized opportunities, a recommended pilot, and a written roadmap—or a documented recommendation not to proceed.
- It requires
- Access to the people who do the work and accurate information about your systems and data.
The call is free because it decides fit, not because the work behind an assessment is quick. Nothing about your systems is analyzed in depth until an Assessment scope is agreed.
Security, documentation, and human authorization apply to every service
Every service group carries the same conditions: what a workflow may reach, what gets recorded, and who authorizes an action that has consequences. These apply from assessment through ongoing operation, including during a pilot.
Security Constraint
A minimum condition for an engagement, not a tier that can be removed to reduce scope or cost.
- Identity and authorization design
- Every workflow begins with who the user is and what that person is already allowed to open. Nothing is retrieved, summarized, or sent on behalf of an identity that should not have it.
- Least-privilege access
- Each identity holds the narrowest access that does the job. Broader or standing administrative access is not requested for convenience.
- Data-flow review
- What enters a workflow, where it travels, which provider processes it, and what is retained is written down and agreed before work starts.
- Tenant and client isolation
- Work built for one organization stays inside that organization’s boundary, and data from one engagement never becomes context for another.
- Secret handling
- Credentials and keys live outside source control and outside anything a model can read, and they are rotated when access changes.
- Provider review
- Where data reaches a model or software provider, terms, retention behavior, and data-use positions are reviewed rather than assumed.
- Retention decisions
- How long a workflow’s inputs, outputs, and logs are kept is decided deliberately, and deletion stays possible.
- Untrusted content
- Email, documents, and web content are treated as untrusted input. Retrieved content cannot change what a workflow is permitted to do or which actions it may take.
Documentation and auditability
Work that cannot be explained after the fact cannot be relied on, so records are written as the work is done.
- Implementation documentation
- What a workflow does, which systems and data it touches, who owns it, what it deliberately excludes, and how to reverse it.
- Logging and auditability
- For actions with consequences, the record shows what happened, what the system proposed, who authorized it, and when it ran.
- Test and rollback approach
- Each implementation is tested before it runs on real work, and a failure leaves the underlying record untouched and reports the error.
Human authorization
Sensitive actions stay with a person, by design, in every engagement—including pilots.
- Accountable approval
- Record changes, payments, and externally facing messages are approved by someone accountable for the outcome before they execute.
- Assistance is not autonomy
- Drafting, summarizing, and classification support a decision; they do not make it, and they never replace the person responsible.
- Approval designed in advance
- Approval points are placed before the workflow runs, and the approver is identified in the record rather than assumed.
Not sure which stage you are in?
Describe the workflow that is costing you time. The call is short, and its purpose is to establish fit and the honest next step—which may be that nothing here is worth building yet.