Your organisation already has the answers. The problem is finding them.
Make your policies, procedures, and institutional knowledge instantly accessible — in the tools where your people already work.
Every organisation accumulates years of knowledge in policies, guides, SOPs, and the heads of experienced staff. The problem isn’t a lack of knowledge — it’s that the wrong person can’t find the right answer fast enough. AI knowledge assistants change that equation, permanently.
Report generation time at NRMA after deploying NRM8, their AI knowledge assistant
Distinct AI personas at NRMA — NRM8, Chatm8, SIXTm8 — each grounded in different knowledge domains
Data sovereignty — every assistant runs inside your Azure tenancy, no data leaves your environment
From Discovery Workshop to first production deployment — not quarters
The knowledge is there. The friction is in accessing it.
Most organisations don’t have a knowledge problem — they have a knowledge access problem. Decades of policy, process, and institutional expertise are locked in document libraries, intranet pages, shared drives, and the minds of long-serving staff. The result is wasted time, inconsistent answers, and decisions made on incomplete information.
The fifteen-minute search
Staff know the answer exists somewhere — in a policy document, an old email chain, a SharePoint folder someone else manages. Finding it reliably takes time they don’t have, so they ask a colleague, who asks someone else. The answer eventually arrives. Fifteen minutes after the moment it was needed.
Inconsistent answers
When the same question gets asked to three different people, three slightly different answers go back out. In regulated environments — insurance, education, aged care, not-for-profit services — that inconsistency isn’t just inefficient. It creates compliance risk and erodes confidence in the institution.
Knowledge trapped in people
In organisations where a handful of senior staff carry most of the institutional knowledge, every departure is a knowledge loss event. New starters spend their first months asking questions that experienced staff find repetitive. The same knowledge gets re-explained, over and over, instead of being deployed once and made accessible permanently.
Outdated documentation nobody trusts
Document libraries fill up. Policies get updated but the old version stays on the intranet. Staff learn quickly that they can’t fully trust the documentation, so they verify with colleagues anyway. The documents exist to be useful; they stop being useful because nobody can trust they’re current.
Staff time misallocated
Subject matter experts — compliance officers, experienced nurses, senior educators, HR managers — spend disproportionate time answering the same questions from colleagues. This isn’t their highest-value work. AI knowledge assistants free them to do the work that actually requires their judgement and expertise.
The new starter disadvantage
New staff start at a significant knowledge deficit. Without fast, reliable access to the organisation’s accumulated knowledge, it takes months to become truly effective. The first person they ask shapes what they believe is true — which may or may not match the documented policy. An AI knowledge assistant removes that lottery from onboarding.
Your knowledge. Instantly accessible. Always sourced.
An AI knowledge assistant connects to your actual organisational content — not the internet — and answers in plain language, from the source, in the tools where your people already work.
Built on Azure AI Foundry and deployed inside your own Azure tenancy. Every answer is grounded in your indexed content and cites the source, so staff can verify. Every interaction stays within your environment.
Connected to your documents
Your SharePoint libraries, policy documents, SOPs, training materials, and knowledge bases are indexed and made queryable. The assistant answers from your actual content — not generic training data — and cites the source document so staff can dig deeper if needed.
Role-based access controls
Different staff see different content. Microsoft Entra ID governs who can access what — a frontline worker gets answers relevant to their role; a manager gets access to additional content. Different personas can be deployed for distinct audiences: staff, students, volunteers, customers.
Where your people already are
Deployed natively inside Microsoft Teams, SharePoint, and web browsers — no new platform to adopt. Staff ask questions in the same interface they use for everything else. That familiarity is why adoption rates are high and why the knowledge actually gets used.
Fully inside your Azure tenancy
Every query, every response, every interaction log stays within your environment. Data sovereignty applies to the knowledge assistant exactly as it applies to everything else in Azure. No shared cloud platform, no data used to train external models.
Active, not static
As your documents are updated, the indexed knowledge updates. Usage analytics show which questions are being asked most frequently — surfacing gaps in documentation and opportunities to improve your knowledge base over time. The assistant gets more useful as you maintain it.
Three organisations. One consistent pattern: knowledge made accessible.
Across insurance, education, and the not-for-profit sector, the underlying challenge is the same — staff spending time looking for answers that should be instant. These are the deployments we’ve delivered.
NRMA Insurance — NRM8, the workplace mate
- ~10minReport generation, was around a week
- 3+Distinct AI personas deployed
NRMA is one of Australia’s best-known membership organisations — a large, operationally complex workforce spanning motoring, travel, tourism, and frontline services. As the organisation grew, staff spent significant time navigating fragmented systems to find information.
Antares deployed QBot inside NRMA’s Azure tenancy — branded through a staff naming competition as “NRM8” (NRMA Mate). The platform now includes the m8 series: NRM8 for general staff knowledge, Chatm8 and SIXTm8 for specific operational functions. Contact centres gained rapid access to accurate customer information. Talent teams had job ad creation automated. Technical teams found document search dramatically faster. Report generation fell from roughly a week to around ten minutes.
Security was non-negotiable: Microsoft Entra ID single sign-on, role-based access controls, and private network endpoints ensure data sovereignty throughout.
“Since its introduction, QBot — known internally as the m8 series — has emerged as a vital enabler in NRMA’s journey toward AI and automation adoption. By fostering greater awareness, championing ethical AI practices, and unlocking enhanced productivity across our business, it’s paving the way for a smarter, more innovative workplace.”Andy McCarthy, GM Technology Engineering, NRMA
Haileybury College — one platform, three audiences
- 3Distinct personas — staff, students, parents
- AzureFully inside Haileybury’s tenancy
Haileybury College presents a challenge common across large independent schools: a complex knowledge landscape spanning curriculum, policy, administration, and pastoral care — with three distinct audiences who each need different information delivered in different ways.
Antares deployed a multi-persona AI knowledge platform on QBot inside Haileybury’s Azure environment. Staff have an assistant grounded in school policies, procedures, and internal knowledge. Students can ask curriculum and admin questions within boundaries appropriate to them. Each persona operates from a separate knowledge scope, with tone and content access calibrated to the audience.
The result is a single platform that serves the whole school community — with governance that ensures each audience only accesses what they should, and that sensitive institutional knowledge stays where it belongs.
Deployed on QBot inside Haileybury’s Azure tenancy — distinct personas for staff, students, and parents, each grounded in the content and access controls appropriate to their role in the school.Production deployment · QBot by Antares · Azure AI Foundry
Mission Australia — 450 programmes, one place to ask
- 2,800+Staff across national operations
- 450Programmes delivering frontline services
Mission Australia is a national not-for-profit delivering around 450 programmes across Australia — homelessness, mental health, family services, and substance dependency support. With 2,800 employees and thousands of volunteers spread across metropolitan and regional sites, keeping a lean IT team and a geographically dispersed workforce connected to current, accurate information is a genuine operational challenge.
Antares has been Mission Australia’s strategic Microsoft technology partner across their digital transition. Building on that foundation, the focus has turned to deploying an AI staff assistant — grounded in Mission Australia’s internal knowledge, accessible to staff wherever they work, and designed to answer the high-frequency questions that currently consume disproportionate time from central teams.
The Microsoft-based infrastructure already in place — Microsoft 365, Azure, SharePoint — provides the platform the knowledge assistant needs to be deployed securely and quickly.
“If we provide people with the most efficient tools and the most efficient ways to do things, that allows them to spend more time with clients. In the future we want to be able to create smarter applications that help us serve clients better.”Peter Smith, CIO, Mission Australia
The same capability. Different audiences, different knowledge, different outcomes.
An AI knowledge assistant can serve multiple different audiences from a single platform — each with their own knowledge scope, tone, and access controls. Here are the most common deployment patterns we see across sectors.
Staff knowledge assistant
Your staff generate more ad hoc knowledge queries than any other audience — HR policy, IT procedures, compliance requirements, financial processes, procurement rules. Most of those queries have a documented answer. The assistant surfaces it in seconds, cites the source, and frees central teams from fielding the same questions repeatedly.
Most useful for organisations with distributed workforces, complex policy environments, or high rates of staff turnover — where consistent, reliable knowledge access is a daily operational need rather than an occasional requirement.
- HR policy and entitlements queries
- IT and system support, first-line resolution
- Compliance and regulatory requirements
- Procurement, finance and approvals processes
- New starter onboarding — consistent, always-on answers
NRMA Insurance (NRM8)Staff across motoring, travel, and frontline services access policies and process documentation via Teams. Report generation time dropped from around a week to about ten minutes.
Haileybury College (staff persona)Teaching and operational staff can query school policies, procedures, and institutional knowledge instantly — without waiting on administration.
Mission AustraliaKnowledge assistant planned for 2,800+ staff across 450 national programmes — grounded in Mission Australia’s service delivery documentation and internal policies.
Student knowledge assistant
Students generate high volumes of repetitive administrative queries — enrolment, assessments, deadlines, campus services, course requirements. Those queries don’t need a human to answer them; they need accurate, instant responses grounded in the institution’s actual policies and content.
A student-facing assistant operates within a defined scope — no access to staff-only content, no access to other students’ data — and is calibrated in tone to match the institution’s approach to student communication. Available 24/7, including the night before an exam.
- Course content and assessment queries
- Enrolment, deadlines and timetable questions
- Campus services and support resources
- Available around the clock, no staff time required
- Consistent answers grounded in institutional policy
UNSW Sydney — where QBot beganDr David Kellermann’s engineering course — 500+ students, 99% satisfaction, pass rates rising from 65% to 85% after deploying QBot in Microsoft Teams.
Haileybury College (student persona)Students access curriculum, administrative, and campus information via a dedicated assistant with appropriate content boundaries — available around the clock.
Newington College (NewAI)QBot platform deployed as NewAI — staff report daily use, with particular value in reducing admin load on teachers and supporting student queries consistently.
Frontline and field worker assistant
Frontline and field workers are often the furthest from where institutional knowledge lives — and the most dependent on having the right answer quickly. Whether it’s a care worker checking protocol on a client visit, a field technician needing a procedure, or a social worker navigating service entitlements, the cost of a wrong or delayed answer is high.
An assistant deployed for frontline staff is typically accessed via mobile — Teams on a phone — and is calibrated for short, action-oriented responses. It pulls from the operational documentation most relevant to fieldwork, rather than the full document library.
- Clinical, care, or service protocols — on the go
- Health and safety procedures for field situations
- Client service entitlements and eligibility criteria
- Mobile-first, short-form answers for field use
- Role-scoped content — each worker sees only what they need
Health and aged careClinical protocols, medication procedures, incident reporting workflows — accessible to care workers in the field without requiring a call to central teams.
Not-for-profit servicesCase workers and support staff across geographically dispersed programmes accessing service entitlements, eligibility criteria, and procedure documentation from a single assistant.
Infrastructure and utilitiesField technicians accessing maintenance procedures, safety requirements, and technical documentation via Teams — without leaving the tools they already carry.
Contact centre knowledge assistant
Contact centre agents handle high volumes of customer queries — many of which require looking up policy, procedure, or product information in real time. When that lookup is slow, average handling time increases. When the answer is inconsistent, customer satisfaction drops and compliance risk rises.
A contact centre knowledge assistant acts as the agent’s co-pilot: surfacing the right answer from policy and product documentation while the customer is on the line, ensuring consistency, reducing escalations, and bringing new agents up to speed faster.
- Real-time policy and product lookup during calls
- Consistent answers, every agent, every call
- Reduced average handling time and escalation rate
- Faster new agent onboarding — days, not weeks
- Audit-logged interactions for compliance purposes
NRMA Insurance (NRM8)Contact centre agents gained rapid, accurate access to policy and product information during customer interactions — reducing the time spent searching for answers and improving first-call resolution.
Insurance and financial servicesProduct disclosure statements, policy conditions, claim procedures and entitlements — consistently accessible to every agent, grounded in current documentation.
Member services organisationsMembership benefits, service entitlements, and operational procedures — surfaced quickly enough to stay ahead of the customer conversation.
Volunteer knowledge assistant
Volunteers present a specific knowledge challenge: they’re often part-time or episodic, may not work closely alongside experienced staff, and have limited access to the informal knowledge networks that full-time employees rely on. They need the organisation’s knowledge to be available on their terms — in the moment, outside business hours, without requiring a coordinator to be on call.
An AI knowledge assistant deployed for volunteers handles the high-frequency questions about procedures, safeguarding, roles, and policies that would otherwise consume coordination staff time — and makes every volunteer feel as informed as an experienced staff member.
- Role-specific procedures and responsibilities
- Safeguarding, safety, and compliance requirements
- Event and programme logistics — on-demand answers
- Available outside business hours without coordinator load
- Consistent, policy-grounded answers for every volunteer
Mission AustraliaA national not-for-profit with thousands of volunteers across Australia — deploying a knowledge assistant grounded in volunteer procedures, safeguarding requirements, and programme-specific information to reduce load on coordination staff.
Not-for-profit sectorVolunteer onboarding, compliance requirements, and operational questions handled consistently — without placing ongoing demand on coordination staff who already carry heavy workloads.
Education and eventsParent volunteers, event support staff, and community helpers accessing the information they need in the moment — reducing coordination overhead during busy periods.
From first conversation to production deployment — weeks, not quarters.
The most common barrier to deploying an AI knowledge assistant isn’t the technology — it’s the absence of a structured starting point. Our engagement model is designed to give you clarity before you commit and something working in production as fast as possible.
Discovery Workshop
Fixed fee · 2 weeks
We map your knowledge landscape — what content exists, where it lives, who needs access to what, and which assistant use cases will deliver the most immediate value. Deliverable: a concrete deployment plan with sequenced priorities and effort estimates.
Knowledge foundation
Typically 2–4 weeks
We prepare your source content — indexing SharePoint libraries and document repositories in Azure AI Search, configuring retrieval pipelines, and standing up your Azure AI Foundry environment inside your tenancy. The assistant has something real to draw from before we deploy it.
First deployment
Typically 4–6 weeks total
First production assistant goes live inside Teams and SharePoint. Role-based access controls configured. Usage analytics activated. The assistant is in the hands of real users, answering real questions from your real content — not a demo, a live production deployment.
Expand and manage
Ongoing sprint delivery
Additional personas, broader content indexing, deeper integrations, and ongoing tuning — delivered in fortnightly sprints by a named team that knows your platform. Usage data drives prioritisation. The assistant evolves as your knowledge base evolves.
We’ve built this for organisations like yours — in production.
The case studies above aren’t representative deployments or controlled pilots — they’re live systems, used daily, by real staff. That production experience is what we bring to every new engagement.
Microsoft-only practice
Over 20 years of Microsoft partnership and a practice built entirely on the Microsoft stack. We use Azure AI Foundry, Azure AI Search, Semantic Kernel, and Microsoft Entra ID on every engagement — because that’s all we do. That depth matters when the architecture decisions get complex and the governance requirements get specific.
Data sovereignty by design
Every assistant we build runs inside your Azure tenancy. Your documents, your queries, your interaction logs — none of it leaves your environment. We don’t offer this as an option; it’s the only architecture we use. For organisations in regulated sectors, that’s not a preference — it’s a requirement.
Sector depth, not just platform depth
We understand what knowledge management looks like inside an insurance contact centre, an independent school, a national not-for-profit delivering community services, and a health organisation operating across distributed sites. That sector knowledge shapes the architecture and adoption approach from the start — not as an afterthought.
Production in weeks
A two-week Discovery Workshop to scope the work. Four to six weeks to a first live deployment. We’ve designed the engagement model specifically to reduce the time between first conversation and something your organisation actually uses — because the knowledge value is in the deployment, not the planning.
Active after go-live
Deploying an assistant and walking away doesn’t work. Knowledge changes, usage patterns surface gaps, new content needs to be indexed, and access controls need to evolve as your organisation does. Our managed service provides ongoing monitoring, content updates, and capability development in fortnightly sprints — with a named Technical Lead who knows your deployment.
Australian, local, direct
Based in Sydney and Melbourne. Every engagement is led and delivered by an Australian team with no offshore handoff. The team that runs the Discovery Workshop is the team that builds the deployment. There’s no account management layer between you and the people doing the work.
Ready to make your organisation’s knowledge actually accessible?
Start with a fixed-fee Discovery Workshop — two weeks to map your knowledge landscape, identify the highest-value use cases, and produce a concrete deployment plan. Or book a 30-minute conversation first to talk through your situation.
We work with organisations across insurance, education, not-for-profit, health, and financial services. Sydney and Melbourne-based team — available for in-person sessions.
Questions we hear at the first conversation.
An AI knowledge assistant is an AI agent that’s connected to your organisation’s existing content — your policies, procedures, SOPs, product guides, training materials, and knowledge bases — and allows staff to get instant, accurate answers in plain language without having to search through documents or wait for a colleague. Unlike general-purpose AI tools, it’s grounded specifically in your organisation’s content, enforces your access controls, and keeps all data inside your Azure tenancy.
Yes. Microsoft Copilot improves individual productivity within Microsoft 365 — helping staff draft emails, summarise meetings, and manage tasks. An AI knowledge assistant is designed to give staff authoritative answers from your organisation’s own content — policy documents, SOPs, internal knowledge bases, operational documentation — with role-based access and full audit logging. The two are complementary and many organisations run both.
Accuracy comes from retrieval-augmented generation (RAG) — the assistant retrieves the most relevant content from your indexed source documents before generating an answer, and cites the document so staff can verify. This means it answers from your actual policies and documentation, not from general training data. Maintaining accuracy over time requires active content management — keeping source documents current and the knowledge base in good shape. That’s part of what our managed service covers.
No. Every AI knowledge assistant we build is deployed inside your own Microsoft Azure tenancy. Your documents, your staff’s queries, and the assistant’s responses never touch a shared platform or leave your environment. The same data governance controls that apply to your Azure environment apply to the knowledge assistant. This is an architectural principle — not a feature you configure.
A first production knowledge assistant can typically go live within four to six weeks. The main variable is the state of your source content — whether your documents are accessible, reasonably current, and organised in a way that can be indexed effectively. Our Discovery Workshop — two weeks, fixed fee — assesses this and produces a deployment plan before you commit to the build. Most clients see their first production deployment within six weeks of completing the workshop.
Yes. A single platform can support multiple AI personas — each with their own knowledge scope, tone, and access controls. Haileybury College deploys separate personas for staff, students, and parents from a single QBot instance. NRMA’s m8 series includes NRM8, Chatm8, and SIXTm8, each serving a different function with a different knowledge base. Microsoft Entra ID governs what each persona can access, so there’s no risk of one audience accessing content intended for another.
A knowledge assistant needs active management to stay useful — your documents change, new content needs to be added, usage patterns surface gaps, and access controls need to evolve. Our managed AI service provides ongoing content updates, performance monitoring, capability development in fortnightly sprints, and monthly roadmap reviews — delivered by a named Technical Lead who knows your deployment. Many clients transition from a project engagement into managed service once the foundation is live.