A lot of our customers are in warehouse distribution, 3PL, manufacturing, retail verticals, and a common pattern that is still true today is that main planning and decision workflows live and breathe through Excel. If you are an organization today, Q4 2026 and still do not have a reliable way to talk to your data and drive decision making with AI you are behind. Now, why aren’t orgs there yet? What is stopping them? Seems like a no brainer state to get into, putting bureaucratic and political reasons that exist in enterprise aside for a moment, this rich data foundation that teams would like to get AI enabled, core systems are often legacy, locked down behind 4 walls, and there is not an easy way to integrate agentic workflows on top of it.
For example, several customers we have are still on IBM AS400 containing their key inventory, master, supply order and sales data. And others are homegrown, custom ERPs, these are not easily accessible interfaces. Requires technical skillset and specific domain knowledge to get value from it, but these are still the key systems of records running enterprises today. It answers why customers are looking into providers like Snowflake and Databricks today, it’s a data consolidation layer to allow for reporting and other downstream processes to access this locked down data. But still even with this, these are generic tooling and providers that solve a deep breadth of use cases.
Our solve with B/eye Fabric is that we build this data harmonization layer to securely build scalable, self healing data infrastructure behind your 4 walls against your AS400 as an example, get the relevant data, build a data model and semantic representation of the data, but then layer in the unstructured data and context on top, this is learned by meeting users where they are, in our case business and supply chain practitioners, operators, inventory analysts, demand/supply planners, finance, understanding their rules and processes and having our analytics harness build this context layer on users’ behalf. As users engage, capturing this rich telemetry data and building this business rule and policy layer so that everyone is going off a single source of truth. A colleague leaves, switches functions, the documentation is persistent, evolving, gone are the days of not knowing why something exists, or understanding why a KPI is defined a certain way, static reporting is a way of thinking of the past (e.g. Power BI, Tableau). Now with analytics harnesses like B/eye, we shorten the distance between questions and answers. Ensuring accuracy, auditability and that costs are controlled. The harness has controls and guardrails in place to ensure data is secure, token spend is not going uncontrolled and that it is a glass box and you see the activity and value users are getting out of the system, so ROI can be measured, not a flying blind approach for which a lot of the general purpose tooling suffers from.
Beyond this, once a robust data layer and context layer is built connected with legacy systems like AS400 in near real time, powerful analytic capabilities using python/SQL is unlocked. A business user does not need to care about this or learning it, goes much further than what an Excel and even advanced Excel users can do today with Power Query/Macros and the like, all a business user needs is the ability to describe what they need and B/eye will build it, bespoke, fit for purpose to the workflow and the need from the business user, not a generic tool for which you need to fit your process around. For example, customers have built suggested order agents to run proactively and as data is changing, the B/eye system picks up on it and spawns and builds a succinct output of what your suggested orders need to be. Other use cases come from forecasting demand, finding anomalies/patterns in sales/inventory data. All this is possible without a technical skillset, driving business value and even better its designed for business teams. Version control, auditability, explainability is all baked in so it is an engine that can be trusted. And continues to grow and evolve as users engage.
And our favorite part, users are having fun. We always believed in that if we can make the non sexy work, fun, easier, freeing up our users time for creative thought and decisions, we have met the mark with our product philosophy. Now, software is never done, it is constantly evolving and our users are pushing the platform forward.