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Enterprise Assistants & AI Automation

AI automation and enterprise assistants for business workflows.

We connect enterprise assistants, document processing, forecasting and decision support to existing interfaces, permissions and approval processes.

Experience dating back to 2011Software and infrastructure projects under the Hosted brand
Data and accessSources, permissions and sensitive-data boundaries are defined at the start of the project
Human oversightEvaluation, logging and approval steps are retained for critical outputs

What does this service deliver?

We connect AI to automation with human review and defined exception paths.

Automation that retains human oversight

Answers linked to their sources

Quality monitored through real usage

What is included?

AI creates value when it becomes part of the everyday workflow.

When AI sits apart from employees' tools and responsibilities, it tends to remain a short-lived experiment. We therefore design the solution around the organisation's data permissions, existing interfaces and decision processes.

Potential use cases include internal knowledge assistants, document and email processing, field extraction, demand or risk forecasting, classification and recommendation systems. Human review, transaction records and feedback mechanisms for uncertain results are defined at the beginning of the project.

Service scope

What the engagement can include

Enterprise assistants

We develop assistants that help employees and customers reach authorised, source-linked information more quickly.

Document and email processing

We build solutions that classify documents, extract fields and start the relevant business workflow.

Demand and sales forecasting

We use historical behaviour and operational data to produce forecasts that support planning, inventory and revenue decisions.

Segmentation and personalisation

We create customer segments from behavioural and transaction data, then connect content and offer rules to those segments.

Planning and resource recommendations

We provide data-informed recommendations for task allocation, capacity, routing and priority decisions.

Human-supervised decision support

We retain the AI output source, confidence information and human approval in the transaction record.

Technologies considered for the project

LLMsRAGOCRForecastingRecommendation systemsHuman review
The final stack depends on your current environment, team and requirements.

Decision guide

When is this service a good fit?

When AI needs to become part of everyday work rather than remain a separate demo.
Current situation

The team spends too much time searching for information

How we approach it

We place assistants in business tools that respect user permissions and show the sources behind their answers.

Intended outcomeFaster access to source-linked enterprise information
Current situation

Documents and requests are classified manually

How we approach it

We connect text processing, field extraction and classification to a workflow with human review.

Intended outcomeAutomated pre-processing for standard documents
Current situation

Planning relies only on historical reports

How we approach it

We add demand, risk or behaviour forecasts to existing decision interfaces.

Intended outcomeForecast and risk signals shown within planning screens
Let us assess the use case, available data and cost of error together.Select the first use case

Frequently asked questions

Common questions about data, quality and production use.

How is this different from a general AI solution?

This service focuses on placing an AI capability into existing tasks, screens, approvals and systems rather than developing a model in isolation.

What happens if the AI produces an incorrect decision?

Confidence thresholds, rule checks, output records and human approval are added to the flow according to the level of risk.

Can it connect to our existing ERP or CRM?

Where APIs and permissions allow, AI output can be used in existing systems as a recommendation, draft, task or controlled automation.

How do we choose the first use case?

We compare use cases with available data, a manageable cost of error and measurable outcomes to select a practical starting point.

How are timescale and cost determined?

Timescale and cost are set after we understand the scope, current systems, integrations, data migration, testing and support requirements. We do not promise a fixed duration or price without this information.

Share your requirements

Let us review the use case and the data available to you.

Use the form to describe the task you need to improve, the data sources that may be available and who will use the output. Our technical team will contact you to assess feasibility.
Current situationGoal and priorityTarget date, if any
Share the detailsThe relevant team will review them
Service of interest
Project stage

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