Agentic AI & Automation
AI agents and automated workflows, built around how your business actually runs.
We design, build and hand over AI agents, workflows and integrations. One process at a time, tested on real examples, with a person approving the steps that matter.
In plain terms
Agents and automation are different tools
- Business automation
- Software that follows fixed rules to move information and trigger the next step. It is the right choice when the rules are clear: it is predictable, inexpensive to run and easy to audit.
- Agentic AI
- Software that uses an AI model to decide the next step of a defined task, within limits you set. It helps when the input varies, such as free-text messages or documents, and it needs a human checkpoint for decisions that matter.
AI agents and task orchestration
AI agents that work through defined, multi-step tasks using the tools they are given, and stop for a person before consequential actions.
The business problem
Many administrative jobs are a chain of small steps: find the information, compare it, fill in a template, update a record, tell someone. Each step is simple, but together they take hours and are easy to get slightly wrong. A general chatbot cannot do this safely, because it has no defined process, no limits on what it may change, and no record of what it did.
Discuss this work with usWhat we build
- Task-focused agents with a written scope of what they may and may not do
- Orchestration of multi-step work, with checks between steps
- Research and data gathering from sources you approve
- Recurring reports, reconciliations and preparation work
What you receive
- A written process definition and agent scope
- Tool access limited to what the process needs
- Activity logs showing inputs, steps and outputs
- A record of what was tested and where review remains necessary
How the workflow operates
An authorized task through to a reviewable result
A team member asks an agent to prepare a weekly status summary.
- Step 1, TriggerTask startedA permitted user or a schedule starts a defined task.
- Step 2, AutomatedScope checkedThe agent confirms the task is within its allowed actions.
- Step 3, AI-assistedInformation gatheredRelevant data is collected from approved sources only.
- Step 4, AI-assistedResult preparedA draft summary or set of proposed actions is produced.
- Step 5, Human checkpointReviewedA person approves, edits or rejects the result.
- Step 6, OutcomeCompleted and loggedApproved actions are carried out and every step is recorded.
Where human oversight applies
- Actions that send, delete, pay or commit wait for approval unless you decide otherwise.
- Uncertain or out-of-scope situations go to a person with the information gathered so far.
Customer enquiry automation
Enquiry handling that categorizes incoming requests, drafts or sends approved responses, and routes each one to the right person with context attached.
The business problem
Enquiries arrive through web forms, email and messaging, often faster than the people responsible can sort them. Simple questions wait behind complex ones, and promising leads go cold while the inbox is triaged by hand. When someone picks a request up, the details have usually been retyped from one tool to another.
Discuss this work with usWhat we build
- One intake for website, email and messaging enquiries
- Categorization and routing under rules you define
- Replies drafted only from answers you have approved
- Follow-up reminders, so open enquiries are not forgotten
- Clear handover to a person, with a summary attached
What you receive
- A map of your enquiry channels and routing rules
- A maintained set of approved answers
- Configured intake, drafting and routing workflows
- Training for the people who review and respond
How the workflow operates
An enquiry from first message to human follow-up
A customer submits an enquiry through a website form.
- Step 1, TriggerEnquiry receivedA form submission arrives with the customer's message.
- Step 2, AI-assistedCategorizedTopic and urgency are identified, with a confidence level.
- Step 3, AI-assistedResponse draftedA reply is prepared from your approved answers.
- Step 4, Human checkpointApproval ruleRoutine replies follow your rules; anything uncertain waits for a person.
- Step 5, AutomatedRoutedThe request and a summary go to the right team member.
- Step 6, OutcomeFollowed upThe conversation is logged and a follow-up is scheduled if needed.
Where human oversight applies
- You decide which replies may be sent automatically and which always need approval.
- Low-confidence classifications go to a person instead of being guessed.
Business process automation
Structured workflows for requests, approvals, handovers and recurring administration, built on the tools your team already uses.
The business problem
Much of the coordination inside a team happens through messages and memory: who asked for what, who needs to approve it, and whether it was done. Requests get lost, managers spend time chasing status, and the same questions come up repeatedly.
Discuss this work with usWhat we build
- Structured intake for internal requests
- Approval routing with the context already attached
- Repeatable processes such as onboarding or purchasing, mapped into steps
- Short operational notifications when something needs attention
What you receive
- A process map with automation points and human checkpoints marked
- Working request and approval flows in your existing tools
- Written operating guides
- Training for the people who use and oversee each workflow
How the workflow operates
An internal request through review to completion
A team member submits a request for equipment or system access.
- Step 1, TriggerRequest submittedA structured form captures what is needed and why.
- Step 2, AutomatedRoutedThe request goes to the right approver with context attached.
- Step 3, Human checkpointReviewedThe approver accepts, rejects or asks for more information.
- Step 4, AutomatedAssignedApproved work is assigned and the requester is told.
- Step 5, OutcomeCompleted and recordedCompletion is confirmed and the history is kept.
Where human oversight applies
- Approvals stay with the people responsible for them.
- Requests and decisions are recorded, so status is visible without chasing.
Application integrations
Integrations between the CRM, forms, finance and operations tools you already use, with monitoring so failed transfers are visible.
The business problem
Most businesses run on several tools chosen at different times for different reasons. Information is copied between them by hand, so records drift apart and no one is sure which one is right. When a transfer fails, the error is usually found weeks later, in a report or by a customer.
Discuss this work with usWhat we build
- Form-to-CRM and CRM-to-operations connections
- Data synchronization with clear rules for conflicts
- Custom API connections where no ready-made connector exists
- Alerts for failed or conflicting transfers
What you receive
- A data-flow map showing which system owns each record
- Working integrations with error handling
- Monitoring and alerts with a named owner
- Documentation for ongoing operation
How the workflow operates
A business event updating connected systems
A signed agreement needs to reach several systems.
- Step 1, TriggerEvent approvedA record is approved or a document is signed.
- Step 2, AutomatedData validatedRequired fields are checked and formats normalized.
- Step 3, AutomatedSystems updatedThe CRM and operations tools are updated in the agreed order.
- Step 4, Human checkpointExceptions reviewedFailed or conflicting updates are flagged for a person.
- Step 5, OutcomeRecords consistentEvery system reflects the same, traceable change.
Where human oversight applies
- Conflicting records are held for review rather than overwritten.
- Failed transfers raise an alert instead of failing silently.
Document and knowledge workflows
Document intake, classification and extraction, plus search across your own documents, with source citations and a review step.
The business problem
Important information sits in contracts, reports, forms and guides that are slow to read and hard to search. Staff re-read the same documents to answer the same questions, and data trapped in PDFs rarely reaches the systems that need it without manual retyping.
Discuss this work with usWhat we build
- Document intake from email, uploads or shared folders
- Classification and extraction of named fields, with confidence levels
- Search that answers from your documents and shows the source passage
- Review queues for anything the system is unsure about
What you receive
- An indexed document collection with access rules
- Extraction workflows and a review queue
- Accuracy measured on a sample of your own documents
- Notes on known limits and where review remains necessary
How the workflow operates
A business document turned into structured information
An agreement or application form arrives for processing.
- Step 1, TriggerDocument receivedA file arrives by email, upload or shared folder.
- Step 2, AI-assistedClassifiedThe document type is identified so the right fields are expected.
- Step 3, AI-assistedFields extractedKey details are extracted with a confidence level for each.
- Step 4, Human checkpointReview queueLow-confidence or missing fields are checked by a person.
- Step 5, OutcomeStructured recordApproved data is written to the target system, linked to its source.
Where human oversight applies
- Extracted data passes a review step before it is written anywhere important.
- When your documents do not contain an answer, the system says so instead of guessing.
Custom AI-enabled internal tools
Focused internal applications with AI features, scoped around one measurable outcome and built to be tested, monitored and maintained.
The business problem
Some problems are specific to how a business works, and off-the-shelf tools cover only the general case. Prototypes are easy to make and hard to rely on: many that impress in a demonstration fail in daily use because they were never tested properly or designed to be maintained.
Discuss this work with usWhat we build
- Internal applications built around a specific workflow and its data
- AI features added only where they help
- A scoped prototype before any larger build
- Automated tests, monitoring and access control
What you receive
- A scoped application specification
- A working application with automated tests
- Monitoring and logging
- The code and documentation needed to maintain it
How the workflow operates
From a defined problem to a maintained system
A business has a specific problem that existing tools do not address.
- Step 1, TriggerProblem definedOne problem and one measurable outcome are agreed.
- Step 2, AutomatedScoped prototypeA small working version tests whether the approach is viable.
- Step 3, Human checkpointEvaluatedYou test it on real cases and decide whether to proceed.
- Step 4, AutomatedHardenedTests, monitoring, error handling and access control are added.
- Step 5, OutcomeHanded overDocumentation and support arrangements are agreed.
Where human oversight applies
- A prototype stage lets you stop early if the approach does not work.
- Access follows the roles and accounts you already use.
Questions
What buyers usually ask
What is an AI agent, and how is it different from a chatbot?
A chatbot answers messages. An AI agent works through a defined task across several steps and can take actions in the tools it has been given, such as gathering data or preparing a record. Our agents have a written scope and stop for a person before consequential actions.
Is every project an AI project?
No. Where the rules are clear, ordinary deterministic automation is the better choice because it is cheaper and more predictable. We add AI only where it helps, such as reading unstructured messages or documents.
Can it work with the tools we already use?
Usually, if the tools provide API or mailbox access. We confirm this during the workflow assessment, before proposing a design. If a tool cannot support what you need, we say so and explain the options.
Which AI models do you use?
We choose per project, based on the task, data sensitivity, cost and your preferences. Where data is sensitive, we agree acceptable providers and settings with you before processing anything.
Will customers know they are receiving an automated reply?
That is your decision, and we recommend being open about it. We can label automated messages and make it easy to reach a person.
What does it cost to run?
Model usage and hosted tools have ongoing costs that depend on volume. We estimate them during solution design, so you can see them before any build begins.
Have a process in mind?
Describe what happens today and what a better result would look like. We will tell you whether AI, plain automation or neither is the right answer.