AI partner for organisations

Put AI to work across your organisation.

GoWise connects AI to the knowledge and standards behind your work, then turns what proves useful into repeatable workflows your people guide and own.

  1. 01Applied training
  2. 02Workspace & knowledge setup
  3. 03Workflow design

Giving people AI is only the beginning

AI works better when it can use your knowledge, standards and decisions.

Task Prepare the monthly leadership report.

Without the right setup · AI used as a chatbot

Context is typed every session

Company context

We report monthly to the leadership team. The summary should focus on delivery, budget, risks and decisions required.

Project context

Use the attached project tracker, finance sheet and last month’s report. The supplier review was moved to Thursday.

Instructions & constraints

Follow the attached reporting format.
Write in concise professional language.
Lead with the executive summary.
Do not use unapproved estimates.

  • Project tracker
  • Finance sheet
  • Last month’s report

Retyped every single session

AI response

Draft complete. I prepared a general monthly summary based on the information provided.

Generic. Not aligned with company standards. Needs corrections.

AI with the right context and memory setup

The right context is already available

  • Approved sources
  • Company standards
  • Reusable methods
  • Project decisions

Available when the task needs it

AI response

Done. The monthly leadership report is attached.

Monthly leadership report · March

PDF · 12 pages

Open report

  • Approved figures and sources used
  • Company format and tone applied
  • Required checks completed
  • Assumptions and open risks made visible

Less repeated prompting. More consistent work.

What we do

Practical AI support, built around your team.

Each engagement combines the support your team actually needs: from practical learning and organised context to personalised workflows.

  • Learn

    Applied training and workshops

    Teams develop practical confidence by applying AI to their own documents, responsibilities and everyday tasks.

    Shared understanding · Better judgement

  • Organise

    AI workspace and knowledge setup

    We make approved knowledge, standards, project history and tools available as usable working context.

    Relevant context · More consistent results

  • Build

    Workflow design and automation

    We turn proven methods into personalised workflows that teams can operate, review and improve.

    Repeatable delivery · Team ownership

Selected work

Systems built around real work.

A selection of systems built through real operational needs, production constraints and completed outputs, not invented use cases.

01Video production

A complete video-production pipeline, set up for each client.

We built it while producing real marketing and training videos, then turned that working process into a reusable client setup.

We set up the pipeline with the client’s visual identity, approved assets, tone of voice and review process. The audience, message and creative direction are then defined for each video.

A team member can brief the production agent in plain language, review the work at key stages and take a video from initial brief to final delivery.

After each video, the client setup is updated with what was approved, what needed correcting and which assets can be reused.
The next production begins with those decisions already recorded.

Shown here · Fire-safety training video

A short excerpt from a training video made using the pipeline.

The production workflow. Brand rules and character consistency are applied throughout. Brief and brand rules inform the storyboard. Images and video are generated, then automatically reviewed and revised before they reach human approval. Requested changes go back to generation and are resubmitted. Approved work moves into final production: voice, motion design, editing and delivery.

  1. Brief &
    brand
  2. Storyboard
  3. AI generationImages + video
  4. AI review &
    revisionCheck · correct · regenerate
  5. Human
    approvalFeedback · revise · resubmit
  6. Final
    productionVoice · motion design · editing · delivery

02Operations

Every meeting starts where the last one ended.

For a growing tech startup, we built a meeting-intelligence system that:

  • turns transcripts into structured meeting records
  • documents decisions and clearly assigns actions
  • updates the task tracker and project history after every meeting

Decisions and follow-up carry from one meeting to the next. Nothing gets lost in between.

  • Structured minutes
  • Decision record
  • Task tracker
  • Team dashboard
  1. Meeting
  2. Decisions
  3. Actions &
    owners
  4. Task
    tracker
  5. Project
    history
  6. Next meetingStarts with the
    full context

The task tracker the meeting loop produces. A workspace header carries the GoWise mark, the project name and a note that it was updated after the 26 September meeting. Tasks can be filtered by person and by department, with counts of open, in-progress and completed work. One task is open: confirm the supplier-review cadence and update the leadership brief, owned by Jordan in Operations, due 30 September, in progress. It shows the current decision, three dated meeting updates, links to the meeting minutes, the project schedule and the decision note, the next review date, and a comment box. Two further tasks are listed below it.

Shown here · The task tracker

Our tool, running in a client’s workspace. The names and content shown are examples.

How we work

Better AI starts with understanding what it can do, and where it fits.

Through practical learning and real use, teams understand AI’s capabilities, organise the context it needs, review results together and develop the workflows that prove useful.

  1. Learn what AI can do, and where it fits

    Outcome: A shared understanding of AI’s capabilities

  2. Connect the right context

    Outcome: A working setup with the right sources, rules and tools

  3. Test, review and improve

    Outcome: Checked results, with each correction improving the next attempt

  4. Build and scale what works

    Outcome: Personalised workflows · People retain final control

From practical learning to lasting team capability.

Why GoWise

From complex projects to practical AI systems.

Nath, founder of GoWise

NathFounder, GoWise

GoWise is led by Nath. He began his career in civil engineering and AEC design management, coordinating multidisciplinary teams on large projects across Europe and Vietnam. That work taught him the importance of reliable information, clear ownership and disciplined handovers.

He later brought the same mindset into fast-moving startups, working with product and technology teams to build and run AI-supported systems across research, documents, meetings, investment preparation and content production.

GoWise brings those two sides of his experience together: the discipline needed to manage complex work and the hands-on experience needed to make AI genuinely useful for organisations.

Common questions

The tools should fit your organisation, not the other way round.

GoWise starts with the tasks, knowledge, systems and responsibilities already in place, then selects and configures the tools that fit.

Is this training, consulting or implementation?

It can include all three, depending on the engagement. We begin with practical learning on real tasks, use the evidence to identify where deeper support is valuable, and build a tailored workflow only when the need is clear.

Do you work only with Claude?

No. A project may involve Claude, ChatGPT, Codex or other approved business tools. The choice depends on the task, your existing technology, data policy and access requirements, not a fixed vendor preference.

Do we need to replace our tools or organise everything first?

Usually not. We start with the systems and approved information you already have, then organise only what the selected work needs. We recommend new tools or connections only when they solve a demonstrated gap.

How do you work with company documents and confidential information?

You decide what is in scope. Before anything is connected or shared, we agree which sources and tools may be used, where information can be processed, and who reviews or releases the result. Your existing policies and permissions remain the starting point.

How do you know what is ready to scale or automate?

We test it on real tasks against trusted sources, agreed standards and human expertise.
Only repeatable steps that perform reliably, have an accountable owner and carry an acceptable level of risk for your organisation move forward. If something does not prove out, we will tell you not to build it.

What does our team have at the end?

A practical way of working your team can run without us: organised context, reusable instructions, agreed review points and, where relevant, a tested personalised workflow.
The handover reflects what proved useful during the engagement.

The tools will change. The way your team works stays yours.

Bring us the work you want to improve.

Tell us where work is repetitive, inconsistent or buried in scattered information. We'll help identify a practical place to begin.

We’ll use your details only to respond to your enquiry. Please don’t include confidential information.