Read
Reads the documents, messages and records that start the work.
AI integration & agent development services
Turn documents, email and requests into reviewable records and actions in your business software. Ekyon builds one defined workflow, with integrations, review controls and handover agreed around the job your team needs to finish.
Check the source and edit the extracted fields.
01One workflow
to start
02Every action
traceable
03Your systems
stay in place
Operating model · 01
The agent is given a clear job, the tools required to do it, and the boundaries it cannot cross. Permissions, agreed review rules and evaluation results determine what can run and what needs a person.
Reads the documents, messages and records that start the work.
Uses your policies, context and examples, not a generic prompt.
Escalates ambiguity and sensitive decisions to the right person.
Updates your systems, closes the loop and leaves evidence behind.
Two ways to build · 02
Our AI agent development services follow two paths. Most teams begin with one existing operational workflow. When the agent itself is the product, we build the larger software experience around it.
Our AI workflow automation service starts with one process your team repeats every week. We define which steps can be automated inside the software you use, how results are checked and when your team takes over.
Compare examples and choose a first workflow
Show us the workflow02
We design agent-native research platforms, operational copilots, vertical SaaS and customer-facing tools where the agent owns part of the experience, not a chatbot added later.
Project evidence
Two different scopes, with concrete work you can inspect before discussing your own project.
Document workflow
Email and WhatsApp collection, structured extraction, editable review, automation rules and accounting exports, brought together in one product.
See the document automation projectChoosing a first scope? Compare document software with a custom workflow
Our own AI product
An AI design product with a custom agent harness, project context and tools that produce editable interface work for design and code handoff.
See the dMaya projectA document’s journey
An example of how a scoped document workflow can move from intake to a reviewed accounting handoff.
Someone opens a file, hunts for context, checks policy, makes a call, enters the result elsewhere, and starts again.
Intake checklist · 03
A good first agent does not need a grand AI strategy. It needs a repeated job, observable judgment and a finish line.
The same shape of work arrives every week.
Documents, email, images or natural language.
Context matters more than if-this-then-that.
People copy information across two or more tools.
Your team can describe what correct looks like.
Time, cost, errors or turnaround can improve.
Sensitive or uncertain decisions can wait for a person.
The software has an API or a workable browser interface.
A useful pilot needs accessible systems, representative examples and an outcome your team can evaluate.
Delivery standard · 04
You receive a working workflow with the agreed integrations, review controls, evaluation checks, documentation and handover.
The real process, exceptions and definition of done.
A defined process, permitted actions and exception paths.
API or browser access to the tools your team uses.
Your policies, examples and operating context.
Thresholds for automatic work and human escalation.
Source information, applied rules and exception notes.
Tests against representative work before rollout.
Agreed hosting, documentation, source ownership and access.
Ways to work together · 05
Begin with representative work and an agreed outcome. Expand the scope only after the first workflow has been evaluated.
Planning ranges in USD, subject to agreed scope, access and available examples. Hosting, model usage, third-party subscriptions and optional ongoing support are budgeted separately. See the AI agent development cost guide
Evaluate one defined process on representative work before expanding.
A production workflow across deeper systems and exceptions.
A product interface and agent tools, with the wider software around them.
Optional monthly support for monitoring, evaluations, policy changes and workflow expansion after the first agent is live.
Discuss ongoing supportFine print · 06
AI workflow automation combines models, business rules and integrations to turn documents, messages or records into defined outputs and actions. Review requirements, permissions and the record of what happened are part of the agreed workflow.
Ekyon covers workflow discovery, custom agent architecture, system integrations, company rules, approval controls, evaluations, deployment, documentation and source-code handover.
Scripts are ideal for fixed steps. Agents fit work with unstructured inputs, contextual judgment and exceptions. If a normal automation is enough, we will say so.
Review requirements are agreed for each action. A workflow may prepare records for review, request approval before a write, or automate permitted low-risk steps. Sensitive or uncertain cases need defined escalation rules.
A narrow workflow your team repeats weekly, with clear examples, reachable systems and an outcome we can measure.
Code ownership, account access and the materials you receive are agreed before the build. Optional support can cover monitoring, evaluations and further development.
Ekyon currently budgets a focused workflow pilot at $8,000–$15,000 USD and 3–5 weeks. These are scope-dependent planning ranges, assuming required access, examples and decisions are available. Hosting, model usage, third-party subscriptions and ongoing support need a separate budget.
We prefer secure APIs when they exist, but agents can also work through controlled browser interfaces. Feasibility depends on authentication, access and the reliability of the target system.
Document workflows are one example. We also scope AI features and custom products around your process, available systems and review requirements. Relevant project evidence helps establish what has actually been built.
Investigate custom work when existing products leave a specific gap in integrations, review controls, business rules or the product experience. Evaluate an existing option first when it can meet the requirements. A custom build can also use existing services where they fit.
Bring the process you want to improve, approximate workload, the software involved and a few permitted representative examples. Identify actions that must require approval and the outcome you want from a pilot. Share sensitive samples only through an agreed secure process.
Your next useful step
We’ll map the loop, pressure-test whether AI belongs in it, and outline the smallest useful first build.