Everything you need to know about Flo.w and working with Emu Analytics.
Flo.w is Emu Analytics' AI-powered operational intelligence platform, built for aviation and rail. It ingests real-time data from across your operation (aircraft positions, stand availability, turnaround status, train movements, and more) and turns that data into situational awareness, predictive alerts, and AI-guided decision support for your control teams.
Rather than showing you what's already happened, Flo.w is designed to tell you what's about to happen and what to do about it.
Flo.w has two tailored editions:
Total Operations Orchestration is how we describe Flo.w's end-to-end role in an operation. Most operations tools focus on one layer: tracking, or alerting, or reporting. Flo.w connects all three. It gives you real-time situational awareness, uses AI to detect anomalies and predict problems before they escalate, and then actively supports controllers with the information and recommended actions they need to make the right call. It's not just seeing the operation; it's actively steering it.
Flo.w is designed to connect to the data sources you already have. In aviation this typically includes ATC feeds, CDM (Collaborative Decision Making) data, ACARS, ground movement systems, check-in and boarding systems, and stand management platforms. In rail, this includes TRUST, DARWIN, NRE feeds, and operator-specific movement data.
Because every client's data landscape is different, we work with you during onboarding to map your sources and ensure Flo.w is ingesting the right signals from day one.
Yes. Flo.w is built on a flexible integration layer that connects to third-party systems via standard APIs, message queues, and data streams. We have existing connectors for many of the common platforms used in aviation and rail operations. Where a bespoke integration is needed, our engineering team builds it as part of the delivery engagement.
Flo.w is primarily delivered as a cloud-hosted SaaS platform, which allows us to maintain it, update it, and scale it to your operational volumes without placing infrastructure burden on your team. We can discuss private cloud or hybrid deployment options for clients with specific data residency or security requirements.
Implementation timelines vary depending on data complexity and the scope of integration required. A focused single-domain deployment can be live in weeks. Larger programmes spanning multiple operational areas or requiring bespoke integrations typically run over a few months.
We start every engagement with a discovery phase to scope the work accurately and agree a realistic delivery plan before any development begins.
Flo.w uses a combination of machine learning models trained on historical and real-time operational data, alongside rule-based logic that captures domain expertise built up over years of working in aviation and rail. The AI layer continuously monitors live data streams to detect anomalies, predict how situations will evolve, and surface the interventions most likely to improve outcomes.
Crucially, Flo.w is designed to support human decision-making, not replace it. Controllers stay in control; Flo.w gives them better information faster so they can make the right call with confidence.
Yes. Flo.w includes natural language query capabilities that allow controllers and operations managers to interrogate live and historical operational data using conversational questions, for example "Show me all EU261-risk flights this morning" or "Which stands have had the most delays this week?" without needing to know SQL or build custom reports.
This significantly lowers the barrier to insight and makes Flo.w accessible to the whole ops team, not just data analysts.
A standard BI tool tells you what has already happened. Flo.w is built for the operational present and the near future. It processes data in real time, surfaces actionable alerts before problems escalate, and actively recommends courses of action. While BI is valuable for post-hoc analysis, Flo.w is designed for the control room, where decisions need to be made in minutes, not days.
Our most detailed published case study is British Airways at Heathrow, where Flo.w delivered £3.1 million in validated annual ROI. This broke down across multiple operational areas:
We have further case studies in development across both aviation and rail. See our case studies page for the latest.
Clients typically begin seeing measurable operational improvements within weeks of Flo.w going live, as real-time alerts start preventing avoidable delays and compensations. The speed and scale of ROI depends on the size of the operation, the number of domains covered, and how actively the platform is used by control teams.
We work with clients to identify the highest-value use cases upfront so the platform is targeted at the areas with the most impact from day one.
Data security is fundamental to how Flo.w is built. We apply encryption in transit and at rest, role-based access controls, and regular security reviews. Emu Analytics operates in sectors where data integrity and confidentiality are non-negotiable, and our practices reflect that. We can provide further detail on our security posture as part of an enterprise evaluation.
Yes. Emu Analytics is UK GDPR compliant. We have a Data Protection Officer, maintain records of processing activities, and apply data minimisation principles throughout the platform. Where Flo.w processes personal data on behalf of a client, we act as a data processor and enter into appropriate Data Processing Agreements. See our Privacy Policy for full details.
You do. Your operational data remains yours at all times. Emu Analytics processes it only to deliver the platform services you have contracted for. We do not use client operational data for training AI models or for any other purpose without explicit permission.
Flo.w is priced as an annual SaaS subscription, typically scoped around the size of the operation, the number of domains deployed, and the level of integration and customisation required. We don't publish a standard rate card because every client's requirements are different. Get in touch and we'll put together a proposal based on your specific situation.
Yes. We often run a structured proof of concept or pilot engagement before a full deployment, particularly for larger programmes where stakeholders want to validate the platform against real operational data before committing to scale. This gives both sides confidence and helps us refine the scope for the full rollout.
Book a demo and we can discuss what a pilot might look like for your organisation.
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