AI Programmes & Partnerships
Understand the options. See how the work could fit your organisation. Send us a brief when you are ready.
A practical guide to AI learning, automation, assistants and delivery partnerships. Explore programme content, example workflows, technical choices and what a first engagement could produce.
Read the overview in a few minutes, then explore the sections relevant to your team. No introductory call is required to send a brief.
Advance AI is a brand of Advance Agility Group.
Choose the help you need
Some organisations need their people to become confident with AI. Others already know the problem and need help building a solution. Many need a combination. We separate these conversations so the proposal matches your goal, rather than asking you to buy a course when you need implementation.
Practical learning for people who need to use AI in their work. Combine foundational concepts, useful prompts, source checking and role-specific exercises. Leaders can explore governance and adoption choices; specialist teams can go deeper into agents and automation. Start with the audience and their tasks, then agree the tools.
Map a repetitive process and decide whether automation is suitable. Agree the inputs, exceptions, permissions, approval points and the result that matters. A scoped discovery or pilot can test the approach before a wider build. Integration feasibility and delivery commitments are confirmed after review.
Explore a conversational assistant that helps authorised users find approved information or interact with a defined workflow. Knowledge sources, access boundaries, citations and human escalation need deliberate design. A demonstration is a starting point for discussion, not evidence that a production integration already exists.
Discuss an AI coach, trainer or engineering contribution for a defined piece of work. Agree responsibilities, required experience, availability and handover before committing. This is a conversation about delivery capacity; named people, placements and start dates are not guaranteed by this page.
Capability that stays with your team
The starting point is the task and the judgement it requires. A good prompt matters, but so do the source material, the quality check and the decision about what happens next. Programmes can combine explanation, guided practice, an applied output and reflection.
For people starting with AI, including adult learners, job seekers and community groups. Explore what a language model does, how to describe a task, improve a response, identify uncertainty and protect personal information.
Practice: turn a vague request into a useful brief, compare two answers and explain which parts need checking. Learners leave with a reusable prompt structure and a verification checklist agreed for the programme.
Explore employability and inclusion · Explore adult learningFor teams working with research, communication, meetings, reports and administration. Explore the difference between drafting, retrieving knowledge and taking an action. Bring approved or synthetic examples relevant to the role.
Practice: produce a source-checked briefing, a meeting-to-actions draft or a reusable workflow guide. Review accuracy, usefulness, effort and the changes a person still needs to make. Discuss an approved prompt library and peer support so practice continues after the session.
Explore small-business programmes · Explore employer-network deliveryFor leaders deciding where AI belongs, who owns it and how to know whether it helps. Connect value, people, process and technology. Cover use-case prioritisation, appropriate autonomy, adoption barriers and the operating responsibilities that follow a pilot.
Practice: create a prioritised opportunity list, a named-owner map and a short adoption plan. An internal champion network, coaching or manager clinics can be scoped where teams need support applying the learning.
Explore coordinated workforce programmes · Browse leadership and governance trainingFor participants with suitable prerequisites who want to explore workflow automation, knowledge retrieval, agents or AI-assisted development. Go beyond a convincing demonstration to think about inputs, permissions, failure states, evaluation and handover.
Practice: design a small workflow or prototype with a test set, a human approval point and a record of limitations. The output is a learning artefact unless production implementation and support are separately commissioned.
Understand the technical building blocks · Explore specialist coursesAn introductory 45–60-minute session, a 90-minute hands-on workshop, an applied half-day or a multi-session learning pathway can each serve a different purpose. These are indicative planning formats, not fixed packages. Agree the audience, devices, accounts, preparation, practice time and trainer availability before booking.
For schools and colleges, align activities with the institution's supervision, safeguarding, accessibility and assessment arrangements. School programmes · College programmes · Train-the-trainer and partner delivery
Illustrative workflow blueprints
These examples turn the offer into something you can assess. They are proposed patterns to adapt, not customer case studies or promises that your systems already connect. Open an example to see the inputs, workflow, outputs and a sensible pilot measure.
The problem: procedures, project notes and decisions sit across documents and conversations. People ask colleagues the same questions and struggle to identify the current version.
Possible output: a referenced answer, a decision brief or a list of information gaps. An organisation's “digital brain” starts with maintained knowledge and clear ownership, not simply uploading every file.
Pilot checks: answer accuracy against an agreed question set, source relevance, outdated-document handling and refusal to expose restricted material. Review unsuccessful questions as well as good answers.
The problem: a decision is made in a meeting or a request appears in a busy channel, but ownership and follow-through are unclear.
Possible output: a daily action review with links back to the original discussion and the task record. Permission to read a channel does not automatically mean permission to monitor every employee or publish a message.
Pilot checks: missed actions, false positives, duplicate tasks and whether owners find the output useful. Confirm communication and privacy arrangements before introducing monitoring.
The problem: enquiries arrive through different channels, replies depend on someone's memory and there is no shared view of the next action.
Possible output: one traceable enquiry, an owner, a follow-up date and a draft response. Booking, email and website channels each need explicit integration and testing.
Pilot checks: saved-enquiry completeness, assignment time, duplicates, delivery failures and the ability to recover a retry without creating another lead.
The problem: a bill, request or handover document has to be retyped into another system, with little visibility of corrections or exceptions.
Possible output: a review screen showing the source beside extracted information, a correction trail and a controlled write to the business system. AI extraction is not the authority for stock, payment or approval.
Pilot checks: field accuracy, correction effort, duplicate documents, source-to-record traceability and recovery after a system timeout. Use synthetic or appropriately approved documents.
The problem: routine admissions enquiries, document checklists and handovers consume time while staff need to focus on individual support.
Possible output: a staff-assistance workflow for routine administration. Admissions, safeguarding, immigration and eligibility decisions remain with authorised people.
Pilot checks: correct guidance, appropriate escalation, response quality and reduced retyping. Learner access and privacy requirements must be established before using real records.
Enough technical detail to ask better questions
The right architecture depends on the task, the systems and the risk. Sometimes a clear template and ordinary automation are enough. An AI model becomes useful when interpretation or generation adds value; an agent needs a defined reason to choose and use tools.
An approved question, document or event.
Relevant information and the user's permissions.
Rules, retrieval and model assistance where useful.
Validation and the required human decision.
A confirmed result, trace and visible exceptions.
Retrieve relevant material from an approved collection and provide it as context when generating an answer. This can make an assistant more relevant to your organisation without assuming it already knows your current policies. Retrieval does not guarantee accuracy: source quality, access filtering, freshness and evaluation still matter.
Ask: which sources were used, can the user access them, and what happens when the answer is absent?
An API exposes specific operations in a system. A connector can make those operations easier to use in a workflow. Model Context Protocol (MCP) provides a standard way for an AI application to discover and interact with exposed tools and context. It does not itself grant access or make every system compatible.
Ask: which actions are read-only, which can change records, and what authorisation is required?
A fixed workflow follows defined steps. An agent can select tools or next steps within its instructions. Use a fixed process where predictability is the priority; consider an agent where flexible interpretation is useful and its choices can be constrained and checked.
Ask: what can it decide, when must it ask a person, and how can the team stop it?
A model can propose fields such as request type, draft text and missing information. Application rules must check required fields, permitted values and business conditions before those fields drive an action. Treat the model's output as input to a controlled process.
Ask: what happens when a field is missing, inconsistent or unsupported by the source?
A system needs to distinguish received, saved, pending, completed and failed work. A stable request reference and duplicate checks help retries recover after an interruption. A failed notification should not erase an already saved enquiry or silently create another one.
Ask: where is the authoritative record, who sees failures, and how is recovery tested?
Use representative examples, difficult cases and expected outcomes to assess the workflow. Review accuracy, human correction, response time and usage cost together. Model changes, new documents and growing volume can change behaviour, so agree review and support ownership.
Ask: what evidence is required before release, and what would cause a rollback?
Possible environments include Microsoft 365, Google Workspace, Slack, Notion, CRM systems and existing operational applications. Discuss native automation, platforms such as n8n or a custom service according to the brief. These are integration options to assess, not a claim that every connector is implemented or approved. Licensing, permissions, hosting, data location and ongoing costs are agreed during scoping.
Technical background: official MCP architecture · n8n's RAG overview. Technology choices follow the use case.
Find your audience
Use these pages as a briefing for your first conversation. They describe adaptable offers, not a list of existing clients or approved partnerships. If more than one audience applies, bring the combined brief and we can discuss a coordinated approach.
Student workshops, careers activities and teacher sessions. Explore age-appropriate practice, access and supervision before choosing a format.
Curriculum modules, specialist teaching and staff development, plus a distinct brief for admissions and administrative workflow discovery.
Specialist modules, delivery capacity, curriculum support and train-the-trainer arrangements with clear quality and ownership responsibilities.
Accessible AI foundations, honest application support, interview practice and practical projects, with learning support built around the cohort.
Applied learning journeys for adult cohorts, including practice, feedback and a clear distinction between commissioned learning and any funded route.
A commissioning brief covering cohorts, delivery responsibilities, evidence, procurement and phased expansion.
Member workshops, employer cohorts, leadership briefings and workflow clinics shaped around local business needs.
Practical skills and discovery for administration, enquiries, marketing and follow-up, starting with a manageable process.
Workforce learning and operational support examples with explicit boundaries around safety, engineering and production decisions.
Enquiry handling, viewing follow-up and maintenance communication, with responsible ownership of property and tenancy decisions.
Illustrative starting points
Start with a staff workshop and one learner project. Agree entry knowledge, tool access and assessment expectations. The first review looks at understanding and evidence of practice before expanding across departments.
Choose one recurring administrative task. Map how it works today, where people make decisions and what a small pilot could change. Compare effort, quality and exception handling using agreed measures rather than a promised saving.
Agree a common introductory programme with local adaptations. Separate learner support, specialist teaching, quality oversight and reporting responsibilities. Test one cohort before deciding whether a repeatable model is justified.
Learning pathways
For people new to AI, begin with useful everyday tasks: writing a clear brief, improving an answer, checking sources and understanding what information should stay private. Offer guided demonstrations where individual tool access is unsuitable. Prior knowledge, language needs and accessibility should shape the pace.
For experienced teams, focus on role-specific workflows, leadership decisions, AI governance, agents or automation. Agree prerequisites and practical outputs before choosing a course. Professional learning and introductory community programmes serve different needs; one is not automatically a progression route or regulated qualification for the other.
If your brief requires a qualification, awarding-body relationship or funded place, raise it at the start. These require a separate confirmed arrangement and should not be inferred from a course title.
From a good idea to a maintained capability
Map the current task, people, systems, volumes and exceptions. Choose a starting point using customer value, effort, feasibility and dependencies. Establish a baseline before promising an improvement.
Proposed outputs: a problem brief, process map, opportunity shortlist and decision on whether a pilot is justified.
Agree source information, permissions, human approval points, expected outputs and failure handling. Separate a learning exercise, a demonstration and a production deliverable in the statement of work.
Proposed outputs: a workflow blueprint, acceptance criteria, sample test cases, responsibilities and estimate.
Test representative cases with authorised participants and approved data. Record both successful and unsuccessful results. Include interruption, retry and human correction rather than testing only the ideal path.
Proposed outputs: a demonstration or limited pilot, test findings, measured baseline comparison and an adopt, revise or stop recommendation.
Agree rollout, staff learning, monitoring, support and change control. Document configuration and escalation. Any managed service, service hours or ongoing enhancement work requires its own agreed scope.
Proposed outputs: user guidance, operational handover, owner training, support arrangements and a review plan.
An unfamiliar tool can expose a process problem rather than solve it. Build understanding with the team doing the work, simplify unnecessary handovers and then choose technology. Training, coaching and consulting can support different parts of that change.
Track review effort and exceptions alongside any time saved. For learning, look at demonstrated capability and later application. For workflow delivery, consider accuracy, completion, reliability and operating cost. Set the measures with the owner before the pilot.
Delivery partnerships
| Model to discuss | Possible contribution | Agree before delivery |
|---|---|---|
| Curriculum add-on | A focused AI module within your wider learner programme, with activities and an agreed review method. | Learner prerequisites, content alignment, assessment boundaries and materials rights. |
| Specialist delivery | A trainer, coach or engineering contribution against a defined gap in your team. | Suitability, availability, supervision, deliverables, access and handover. |
| Train-the-trainer | Prepare your staff to use agreed activities and explain the concepts confidently. | Staff readiness, practice and feedback, content reuse, updates and ongoing support. |
| Partner-led or co-branded | A coordinated programme under agreed branding and customer arrangements. | Customer ownership, commercial terms, quality oversight, learner support and intellectual property. |
| Commissioned workforce programme | A pilot cohort or phased programme shaped around a commissioner or employer-network brief. | Procurement, recruitment, any eligibility checks, reporting, budget and responsibilities. |
These models are options for discussion, not existing approvals or agreements. Formal qualification and funding routes require separate confirmation. A strong programme design is useful preparation, but is not proof of an awarding relationship or funded entitlement.
Delivery options
Discuss a focused introduction, role-based workshop or sequence of applied sessions. Agree group size, starting knowledge, trainer preparation and feedback. Live online, on-site and blended options depend on the audience and availability.
Bring a process that causes repeated effort or missed handovers. We can discuss a discovery brief and, where suitable, a limited pilot. Confirm integrations, security boundaries, support and acceptance criteria before implementation.
Discuss specialist modules, trainer or coach support, and a repeatable delivery model under an agreed partner arrangement. Confirm who recruits learners, owns the customer relationship, provides support and handles quality assurance.
A practical briefing
Tell us who the programme or solution is for, their starting point and what should be different afterwards. An approximate group size, delivery location, timing and budget range help shape a realistic option. If these are still undecided, tell us what needs deciding first.
Explain the systems involved, what access may be possible, who approves the work and any procurement or accessibility requirements. Use fictional examples at this stage. A named internal owner helps the proposal address the actual process and its exceptions.
From conversation to proposal
Use a short introductory call to identify the audience, problem and likely type of support. We may recommend a learning session, discovery work, a partner conversation or a different route if the brief does not fit.
Request a tailored outline covering objectives, suggested activities, delivery approach, responsibilities and the information needed for a quote. Any staffing, tool, integration and commercial assumptions should be visible before agreement.
Agree what will be reviewed after delivery: learner work, feedback, workflow reliability or another relevant measure. Use that review to decide whether to expand, adjust or stop. Attendance alone is not proof of workplace impact.
Explore the wider offer
Advance AI is a brand of Advance Agility Group. Gaurav Rajwanshi is a transformation coach, trainer and AI practitioner. Start a conversation with Gaurav and Iva about the people you support and the work you want to improve.
Our published AI training catalogue includes learning in generative AI, leadership, automation and governance. We use that wider portfolio as a starting point for a tailored discussion; course availability, prerequisites and any credential must be checked for the exact programme.
Ask us to explain the proposed delivery team, relevant experience, sample activities and how progress will be reviewed. Any references, trainer checks or partner assurances must be confirmed for your engagement.
Scope, cost and ownership
For learning: audience size, preparation, depth, delivery format, location and materials. For implementation: process complexity, integration access, data quality, testing, deployment and support. Third-party licences and usage costs should be visible separately. Pricing follows an agreed brief; this page does not offer a fixed-price package.
Request a written outline naming the deliverables, exclusions, acceptance criteria, responsibilities and payment milestones. Confirm which materials, code, configuration and documentation you will receive, together with permitted reuse and any third-party licence obligations.
Name the business owner, source-information owner and technical support contact. Agree who handles errors, access changes, usage bills, updates and exit or handover. A pilot is not automatically a managed service or a guarantee of uninterrupted operation.
A named sponsor, someone who understands the day-to-day process, representative examples, access to the right decision makers and time for review. For technical work, identify your system administrator and any security or procurement review. For learning, share audience needs, account/device access and staff support arrangements.
Start with a redacted or fictional example. Do not email passwords, personal records or confidential datasets. We can agree a suitable information-sharing route after the brief is understood.
Questions before we start
Yes, a combined brief can be discussed. The learning scope and technical scope should each have clear owners, deliverables and acceptance criteria. A training session does not itself include a production automation.
The booking link is for a 15-minute introductory conversation. Detailed discovery, programme design and delivery are separately scoped; price and commitments are agreed before work begins.
No. Introductory activities can be designed for non-technical learners and leaders. Specialist engineering and automation work require an appropriate technical brief and different prerequisites.
A partner-led or co-branded arrangement can be discussed. Branding, intellectual property, responsibilities, quality review and commercial terms must be agreed in writing. No existing white-label agreement is implied.
No funding, accreditation, regulated qualification or provider approval is promised on this page. Ask about your specific requirement so the proposed route and any necessary approvals can be checked before promotion or enrolment.
No. Specialist availability and delivery dates are confirmed during scoping. Learning and workflow improvements depend on the agreed scope, participation, systems and operating conditions.
Share your organisation, intended audience, goals, group size, timing and preferred format. Describe the problem without sending sensitive records. Iva and Gaurav can use that brief to discuss the next step.
Start without a meeting
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Include the audience, the task or learning goal, your current tools and what a useful result would look like. Approximate answers are fine.
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Let's talk
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