Skip to main content

    Services / Office AI & Private Deployment

    An office AI assistant with a clearly defined job.

    A Jarvis-style assistant for your business: find approved information, prepare useful drafts and carry out agreed actions. Choose local, on-premises, cloud or hybrid deployment around your data, workload and support needs.

    Start with one task your team repeats: finding a current procedure, preparing an internal summary or drafting a follow-up. We scope the information the assistant may read, the actions it may take and where a person must approve. Then we assess the model, hosting and hardware needed to operate it.

    If this sounds like you

    Who is this for?

    A UK business owner or operations lead evaluating an office AI assistant, local LLM or on-premises deployment for one useful internal workflow.

    How fast?

    Start with one workflow and access review. A pilot delivery window is agreed after checking data, integration and hardware dependencies.

    What will it cost?

    A written quote for the agreed assessment or pilot, with hardware supply, provider usage and ongoing support identified separately.

    What result should I expect?

    A practical deployment decision and bounded assistant scope, with permissions, workload evidence and an accountable operating owner.

    A promise of automatic security, unrestricted staff-data access or guaranteed hardware performance before workload testing.

    The problem we hear

    What should your office assistant know, and what should it be allowed to do?

    Useful knowledge is scattered

    Staff search documents, inboxes and business systems to answer the same operational question. A first workflow needs approved sources, current versions and a named owner.

    Answers and actions are mixed together

    Reading a procedure, drafting a message and sending it have different consequences. Define each level of access before connecting the assistant to business tools.

    A local model is only part of the design

    Connectors, logs, backups and optional cloud services can cross the data boundary. Decide what must stay on-premises and document every external dependency.

    Hardware is bought before the workload is clear

    Model size, context, concurrent users and response-time needs affect capacity. Test representative work before agreeing a hardware specification and running costs.

    How we approach it

    01

    Choose the first office task

    Map one question or handoff, its approved sources and the person responsible. Record the current effort and quality so a pilot has a meaningful comparison.

    02

    Separate answers, drafts and actions

    Agree read-only access, draft preparation and approved actions separately. Set role permissions, review points and a clear route for missing or conflicting information.

    03

    Match deployment and hardware

    Compare local LLM, on-premises, cloud and hybrid options against the workload and data requirements. Where hardware is needed, scope selection, supply and deployment in a written quote.

    04

    Test and hand over ownership

    Check source accuracy, access isolation, review effort, response time and recovery. Agree updates, backups, support responsibilities and a decision on whether to expand the pilot.

    What good looks like

    A defined office-assistant workflow with approved sources and a responsible owner.

    Separate permissions for read-only answers, drafts and approved actions.

    A documented hosting choice and map of any external data flows.

    A scoped hardware specification and written supply quote where required.

    A pilot evaluation and support plan covering quality, effort, cost and recovery.

    What your office AI setup can include

    Internal knowledge assistance

    Answers over agreed documents with source references, existing role boundaries and a human route for uncertain information.

    Local and on-premises LLMs

    Model and runtime assessment for hardware you control, with workload testing and explicit checks on connected services.

    Cloud or hybrid deployment

    A comparison where some tasks may use hosted services, with provider handling and permitted data flows agreed in advance.

    Hardware selection and supply

    Workload-led specification, supply and deployment by written quote. Availability, pricing, support and delivery are confirmed for the agreed configuration.

    Controlled business actions

    Drafts and tool integrations with defined permissions, approval points and exception handling rather than unrestricted access.

    Operating support

    Named responsibilities for source updates, monitoring, backups, software maintenance and incident recovery.

    Illustrative workflow scopes

    Illustrative scope: find the current office procedure

    Illustrative scope, not a completed client case study.

    For a team searching several document stores, a pilot could answer a bounded operational question using approved procedures and show the source. Missing or conflicting guidance would go to the document owner. Answer quality and staff review effort would be measured before expansion.

    Illustrative scope: prepare an internal handover

    Illustrative scope, not a completed client case study.

    For a team preparing a recurring status update, an assistant could assemble a draft from permitted records for a colleague to review. Sending the update or changing a source record would require the authority agreed for that workflow.

    These examples explain possible scopes. Suitability and results would be established through assessment and testing.

    Frequently asked questions

    What do you mean by a Jarvis-style office assistant?

    It is shorthand for a helpful office assistant that can work with agreed information and tools. It does not imply an affiliation with another product or character. The proposed system is scoped to your business, including what it can answer, draft and do.

    Can you run a local LLM on our premises?

    We can assess and scope a local or on-premises deployment. Suitability depends on the model, task, data, users, hardware and support requirements. We test representative work and identify any cloud dependencies before agreeing the implementation.

    Is local hosting automatically secure or fully offline?

    No. Local hosting changes where the model runs; permissions, connectors, logs, backups, updates and network exposure still need attention. A fully offline requirement must be stated and tested across the whole workflow.

    Can you supply the hardware too?

    Hardware selection, supply and deployment can be included in the written scope. We agree the configuration, availability, price, delivery and support before an order. No particular model, performance level or stock position is promised at the enquiry stage.

    Will the assistant have access to everything?

    Access is agreed by source, role and action. Read-only answers, drafts and actions are treated separately. Sensitive actions require the approval and audit trail specified for the workflow; broad machine or mailbox access is not assumed.

    Who looks after it after installation?

    The scope identifies who maintains documents, permissions, models, software, backups and connected services. Monitoring, support cover and recovery responsibilities are agreed before handover.

    What does the first step cost?

    The first conversation identifies one workflow and its constraints. We then agree an assessment or pilot scope, timing and price in writing. Hardware, provider usage and ongoing support are itemised where applicable.

    What would you ask your office AI assistant to do first?

    Bring one repeated task, the systems involved and your local or on-premises requirements to a free discovery call. Use redacted examples. We will scope the assessment, any hardware supply and a practical next step before chargeable work.

    Book Your Free Discovery Call