Everything you need to know about Fronterio

Fronterio is the AI Transformation Platform. It finds where AI can create real value in your company, helps you prioritise the highest-value opportunities, coordinates delivery with the people and the governance built in, and proves what the work actually returned.

Frontier Twin is a living digital twin of your organisation. It connects your business functions, the processes inside them, the roles and systems each step touches, and the AI opportunities, initiatives and measured outcomes attached to that work. It is not an org chart: it models how the work happens rather than who reports to whom. Switch between Current and Frontier to see the same organisation as it runs today and as it could run redesigned around AI. Frontier Twin opens on Pro and above.

Most organisations have already bought AI. Licences are live, pilots are running, and expectations are high. What is missing is the connection between that spend and business value. Usage sits in one tool, governance in another, and nobody can show the board what actually changed. Fronterio closes that gap. It finds where AI can create value, turns the strongest opportunities into managed initiatives, drives adoption with the people affected, keeps every AI system governed, and measures the result.

Mid-market and enterprise organisations that want AI to actually deliver value: AI leads, CIOs, compliance officers, executives, and the employees using AI every day. Ownership usually sits with the person answerable for AI results — a COO, CIO, AI lead or transformation office. Leadership reads the reports, and employees take part in adoption without needing a seat. Every dashboard adapts to the person looking at it.

No. Governance and compliance are built in, but Fronterio is the AI Transformation Platform. It spans the full loop: understand how work gets done, prioritise what matters, transform the work, and prove the result. Compliance is the floor, not the whole product.

No. Fronterio is the layer that makes those investments work. Your teams keep using Copilot, ChatGPT, Gemini, Claude and the agents you build. Fronterio reads usage from Microsoft, Google and Anthropic connectors, keeps every AI system — from any vendor, including self-hosted models — in one governed register, and connects all of it to initiatives, owners and measured value. It works with your AI ecosystem rather than asking you to replace it.

Yes — a strategy document is where most programmes stall. Fronterio is built for what comes after the slide deck: naming the opportunities with a value on each, ranking them in Opportunities, delivering them as initiatives with owners, and verifying what came back. If you want the strategy layer too, Fronterio drafts a canvas, roadmap and OKRs from your own data. They feed the ranking rather than compete with it.

You answer a short readiness assessment during signup, and the results page is your first deliverable. It shows your readiness score benchmarked against published research, a value scan of where the hours are in your kind of work, and your next moves — three ranked moves that always include a quick win you can finish the same day. You also get a board-grade report you can share with leadership through a secure link. No charge, and no setup project.

You get your first directional numbers in about fifteen minutes. Turning one of them into a prioritised initiative with a named owner takes a few days. A verified outcome takes as long as the work itself, usually a quarter. Fronterio moves you through milestones you have actually reached, not a fixed calendar.

From the work, not the tools. The AI Value Scan ranks where the hours are in your company, grounded in your industry, size and assessment. You can then map a real workflow — volumes, minutes per case, cost — and Fronterio prices the opportunity in it. On paid plans, a weekly radar suggests initiatives that fit your context, and a quarterly pulse asks employees what eats their time. Every opportunity arrives scored, so it can be compared.

The value scan proposes where AI saves hours, grounded in your assessment, initiatives and tool spend. The platform then prices those hours itself: hours × people × your hourly cost × weeks per year. The rate and headcount come from your own value model, and defaults are labeled until you set them. A figure that can't be computed shows as hours with a request for your team size — never a guess. Accepted lines become initiatives, and pilots track the hours actually saved.

Every opportunity becomes a comparable case: the value, the confidence, the feasibility and the evidence sit side by side, with risks and prerequisites named. They rank in Opportunities — a single prioritised list of what to pursue next, drawn from your opportunities, initiatives and signals. Each item says why it is there. That is the list your leadership team works from, instead of a roadmap beside the roadmap.

You accept one. An accepted opportunity becomes an initiative: one managed object carrying the owner, the milestones, the tasks and the prerequisites. The people side travels with it — onboarding, training, champions and communication for those affected. So does governance: risk classification, policies, oversight and EU AI Act obligations attach to the initiative they belong to. Work with a value and no owner is a wish with a number attached.

Every initiative carries a shortlist of ways to deliver it. Fronterio researches the market each week and keeps a catalogue of what is available. That covers capabilities inside platforms you may already license, non-software routes like process redesign, governed AI agents, products from vendors, and services from your own implementation partner. Paths are ranked by how well they fit the work. What you already pay for is preferred when the fit is comparable, and a solution only counts as already owned when we can see the licence or the spend behind it. Saying which platforms you run helps the match, but it never earns a top place by itself. Where nothing you own fits, you get the alternatives with their data residency and the source we found them in. Fronterio takes no money from vendors, so the order answers your question and not a sales target.

By keeping estimates and measurements apart. An estimated value is priced from your own volumes, rates and workflows, with assumptions labelled. A realised value is tracked against the baseline as the change lands. A verified value is the strictest tier: it requires a baseline, an actual, an explicit formula, evidence, a period and a named validator — all six, with no exceptions, and no AI can mark a value verified. Leadership always sees which tier every euro belongs to.

Reports built to be forwarded, not dashboards someone has to remember to open. Fronterio generates leadership artifacts on a cadence, each assembled from the same figures the screens show: the AI Value Brief you can send to a budget holder, a monthly AI Transformation Report, a quarterly Board Pack with a secure external share link, and an Annual AI Value Report. The report and the platform cannot disagree, because they read the same numbers.

By treating adoption as behaviour change, not course completion. Adoption is included in every paid plan, for your whole company. Each employee gets My work — a personal view of AI in their own job — plus role-based lessons, a shared prompt library and Ask Fronterio, in eight European languages. Managers get a rollout comms kit, a monthly culture pulse and champions. And because usage data flows in from your AI tools, you see whether behaviour is actually changing, not just who finished a course.

Your usage data usually shows that a handful of people are already far ahead. Fronterio turns that into a working network: nominate champions from your team, give them a ready-made playbook of proven motions, and track the activity that follows — prompts shared, demos run, colleagues helped. A department scorecard shows where the network is thin. Champions are how adoption spreads peer to peer instead of top down.

Yes — a stalled rollout is one of the most common starting points. Fronterio shows per-app Copilot usage from your own tenant, so you see who has gone quiet and which licences sit unused. Then it works the causes: role-based lessons and Ask Fronterio for the people who never got past the demo, champions beside them, a comms kit for managers, and a monthly pulse that surfaces the real barriers. Adoption is measured from real usage, so you see the recovery.

Yes. Connectors for Microsoft Copilot, Google Gemini and Anthropic Claude sync usage daily, so adoption is measured from what people actually do, not what they report. You see engaged users, per-app deltas and department differences, and the licence-waste view shows what you pay for that nobody uses. The monthly AI Transformation Report puts the trend in front of leadership.

Yes (Pro and up). The Teams Agent brings Ask Fronterio, the prompt library, lessons and learning progress into Microsoft Teams. Your people chat with it, search prompts with @Fronterio, and get their next lesson without leaving the tool they already work in.

With one register and one rule: every AI system has an owner. Tools, models and agents are registered, risk-classified and approved through a defined workflow, with policies, human-oversight plans and incidents attached. Every material action lands in an append-only audit log. And governance is not a separate compliance project: obligations, risk and evidence attach to the initiatives and systems they belong to, so the work of governing AI happens inside the work of using it.

Yes. Agents are first-class citizens: each is registered with its purpose, model and data access, classified for EU AI Act risk, approved by a named human, and monitored over its lifecycle. Fronterio does not run your agents. It decides and documents — the compliance check, the guardrails, the approval — and on Enterprise it hands the approved agent to the platform that executes it, such as Azure AI Foundry, Microsoft Copilot Studio or Claude Managed Agents, keeping the evidence file.

Yes — that is the AI Systems register: what is running, where, under whose ownership, with what risk and what evidence. On Enterprise it becomes the connected estate: read-side integrations discover agents and usage across platforms like Microsoft Copilot Studio, Azure AI Foundry, LangSmith and Claude, and self-hosted gateways can push their inventory in. Anything unaccounted for is one click from being registered, classified and owned.

Enterprise visibility into the AI nobody told you about — built on ingestion, not endpoint scanning. Fronterio correlates signals you already have — Microsoft Purview, DLP and network exports, and your declared tool inventory — anonymises user identifiers, and proposes what it finds straight into governance, so unsanctioned tools become registered, risk-classified, and owned.

Yes. The audit log is append-only — entries can be added but never edited or deleted, enforced at the database layer. Deployer obligations carry a status, an owner and evidence links. Risk classifications, impact assessments, policies and incidents live on the record of the system they concern. And all of it exports as branded, regulator-ready PDFs: the compliance snapshot, FRIA records, obligations status and the audit digest. When someone asks, the answer is a document, not a scramble.

Yes. Most customers are deployers — they use AI rather than build it — so Fronterio operationalises deployer duties: risk classification for every system, the Article 26 obligations checklist with owners and evidence, Fundamental Rights Impact Assessments, AI literacy records, transparency disclosures and a serious-incident workflow, on top of the append-only audit log. For teams that build their own high-risk AI, Enterprise adds the provider obligations suite. The framing is readiness: stay well-governed, with the evidence to show it.

When you register an agent, a structured questionnaire maps its purpose and capabilities to the four EU AI Act categories: unacceptable, high, limited, minimal. High-risk agents trigger additional required fields: conformity assessment, human oversight plan, transparency requirements, technical documentation links.

Yes. A guided wizard (Article 27) walks you through purpose, affected groups, fundamental-rights impact, mitigations, and oversight. Ask Fronterio can draft the full FRIA based on your agent data. Export as PDF for regulators.

The AI Literacy tracker records which staff have completed training, when, and the training source. Link it to employee learning paths for end-to-end evidence, from curriculum to individual completion certificates.

No, and treat any tool that promises that with suspicion. Compliance depends on which AI systems you run and how your organisation actually uses them. What Fronterio does is make the work operational: it structures the obligations, assigns owners, keeps the register current and preserves the evidence, so you can demonstrate what you did and when. Fronterio does not provide legal advice. For questions of legal interpretation, involve your counsel.

Customer data is stored in the EU (Frankfurt) and the application runs in EU regions. AI features send organisational context — scores, aggregated metrics, structural facts, and what you type to Ask Fronterio — to AI model providers under Standard Contractual Clauses, and those providers may process it outside the EU. The platform never includes employee personal data in that context, and your conversations are not used to train models. Customers who buy through the Microsoft Marketplace have their AI calls routed through Azure in the EU (Sweden Central).

No. Fronterio does not train models on your data, and your conversations with Ask Fronterio are not used to train the models behind it. What leaves the platform for an AI request is bounded by design: aggregated scores, anonymised metrics and organisation-level context, never employee personal data. Peer benchmarks are computed on data that carries no organisation identity and only surface once at least 15 organisations are in the pool, and you can opt out of contributing entirely.

Fronterio is built to meet GDPR requirements: customer data stored in the EU, a DPA on request, full data export (JSON) and deletion, cookie consent, a published privacy policy, and a documented sub-processor list. The platform never includes employee personal data in the context it sends to AI models — only aggregated scores, anonymised metrics, and org-level context.

Every table is protected by row-level security scoped to each organisation, enforced at the database layer rather than in application code, so isolation holds even if app logic has a bug. Partners see only their own customers, system admins run on their own access path, and customer users see only their own organisation. Cross-tenant leakage is impossible by design.

Yes, from the Business plan. SAML SSO via any IdP (Entra ID, Okta, Google Workspace, etc.), SCIM for user provisioning, optional MFA enforcement, and SSO-enforced login. It's self-serve: org owners configure it themselves in Settings, no support ticket.

Only what each integration needs, and nothing by default. The Copilot adoption tracker uses read-only Microsoft Graph reporting permissions, granted by your admin through standard Entra ID consent. Optional Enterprise integrations — Copilot Studio discovery, Purview sensitivity labels, SharePoint publishing — each request their own scopes, which your admin approves separately. Every permission, endpoint and data flow is documented publicly on the Microsoft data access page, so your security team can review it before consenting.

Yes — and the review materials are public. Data is encrypted at rest with AES-256 and in transit with TLS 1.3, stored in the EU, and isolated per organisation at the database layer. Access is role-based, with seven organisation roles enforced server-side on every request. SSO, SCIM and MFA enforcement come with Business and Enterprise. Infrastructure partners are SOC 2 Type II certified, ISO 27001 is on our roadmap, a DPA is available, and the sub-processor list is published.

The AI Value Scan, end to end. The AI Readiness Assessment with research-backed benchmarks, three runs a quarter. A breakdown of where the hours are. One real workflow priced, one Priced Move accepted, and a shareable AI Value Brief. Plus 25 Ask Fronterio messages a month. No charge during the private launch.

No, because there is nothing to buy. Fronterio is in private launch: approved organisations receive access to the complete platform at no charge for the duration, with no payment details and no time-boxed evaluation. It is not a limited tier and not a testing programme — it is the product, used for real work.

Not during the private launch. There is a single access state: approved organisations receive the complete platform. Every capability described on this site — the Frontier Twin, Opportunities, governance and compliance, the estate integrations, verified value — is included.

Fronterio is a commercial product and will be sold commercially in time. During the private launch that is deliberately paused: no subscriptions are offered and no prices are published. Organisations admitted now are told well in advance of any change, and nothing converts to a paid plan automatically.

A platform seat is for someone running the AI programme: owners, admins, AI leads, department leads, contributors, and viewers. Seats are what plans cap — 3 on Free, 10 on Pro, 50 on Business, unlimited on Enterprise. Employees are everyone else: on every paid plan they take part in adoption — My work, lessons, prompt library, Ask Fronterio — at no per-seat charge and without using a seat.

There is no billing during the private launch. No payment details are collected, no subscription is created and nothing can be purchased on this site. Access is granted by request and can be ended by either side at any time.

The connected estate. Enterprise connects Fronterio to everything your company runs AI on: estate integrations that read agents and usage from your platforms, provider obligations (Article 16) for teams building their own high-risk AI, AI Vendor Resilience, the Brain API, Shadow AI visibility from ingested signals, SharePoint sync, SSO/SCIM, unlimited users and agents, a dedicated CSM, custom integrations, higher message limits, and an SLA. Pricing is custom.

Yes. Every part of Fronterio runs self-service, and organisations that want help can be supported through their own advisers or through guided onboarding from us. During the private launch there is no reseller programme and no commercial partner arrangement in operation.

Copilot is a capability. Fronterio is what turns capabilities into business results. It shows where Copilot use is real and where licences sit idle, drives the behaviour change that gets stalled rollouts moving, decides where AI belongs beyond the Microsoft stack, and puts a verified value on what changed. Microsoft tells you what its own tools did. Fronterio answers the question your board asks: what did all of it return?

Use them — Fronterio reads from them. But vendor dashboards stop at activity: who used which app, and how often. They cannot say which business initiative that use served, what it was worth, or what to do about the people who went quiet. And each vendor only sees itself. Fronterio combines usage across Microsoft, Google and Anthropic, ties it to initiatives with owners, and reports outcomes — because activity is evidence, not value.

You can start there — most companies do, which is how we know where it ends. A spreadsheet holds a list. It does not pull live usage from your AI tools, keep an approval trail a regulator will accept, chase owners, recalculate value when your rates change, or tell leadership what changed this month. Every quarter it drifts further from reality, and the person maintaining it becomes the single point of failure. Fronterio is the system that stays current on its own.

You can, and many companies do — Fronterio even ships with certified partners who deliver it alongside you. What a consultancy alone typically leaves behind is a long engagement and a slide deck that starts drifting the moment it is signed. Fronterio produces the same artifact types — canvas, roadmap, OKRs, board pack — drafted from your own data in minutes, kept live as the data changes, and owned by your team. The strategy belongs to you, not to a firm's template library.

Governance tools stop at the register: systems listed, risks classified, policies filed. Fronterio treats that as the floor. The register is connected to the transformation it exists to protect — every obligation attaches to a real initiative, every risk to a system with an owner, and the same platform carries the adoption work and the value evidence. Governance that lives beside the work becomes shelf-ware. Governance that lives inside the work stays current, because the work keeps it honest.

An LMS measures course completion. Fronterio measures whether behaviour changed. Lessons and Ask Fronterio are part of adoption, but they are means, not the product: every learning surface is connected to real usage data from your AI tools, to champions who spread what works, and to the initiatives the skills are for. When training ends and usage does not move, an LMS reports success. Fronterio reports the truth.