Generative Business Intelligence FAQs: Answers for Mid-Market Teams

Generative Business Intelligence lets business teams ask questions in plain language and get answers they can trust. Beye sits a layer above the systems you already use, brings data from those systems into one place and models it to how your business actually works. Under the surface we handle the data work that used to take analysts days, and in the workspace you see clear answers and simple scenarios so you can move from question to decision faster.

Beye is a good fit when important decisions depend on data but the current process is slow or manual. Typical signs are reports that live in spreadsheets, analysts spending hours pulling data from different systems, or business teams waiting days for someone else to answer a simple question. We focus on distribution, logistics and manufacturing where operations, supply chain and finance teams are wrestling with siloed, messy data and need a more approachable way to get to answers.

Yes. Most customers do not come in with a perfect use case mapped out. We spend time with operations, supply chain and finance practitioners to see how work is actually done today, where people are pulling reports by hand, chasing spreadsheets or waiting days for answers. Using a simple scorecard we highlight high fit opportunities where an AI native approach can help, especially manual, time intensive or siloed analytics workflows. Together we pick one high impact decision workflow, define success in business terms and use that as the starting point for Beye. If you want help shaping a broader roadmap, our Beye Pro services team can act as a fractional chief AI officer and implementation partner.

No. You do not need perfect data or a new data warehouse to get started. Most teams begin with exports from the systems they already use such as WMS, TMS, ERP and spreadsheets. We work with your team to understand how the data is used today, what the key KPIs and business rules are, and then Beye joins, cleans and organizes that data so it is ready for decision workflows.

Beye commonly works with warehouse, transport and ERP systems along with files and exports. Examples include Softeon and other WMS platforms, TMS and ERP systems, plus CSV, Excel and similar formats. Most customers start with secure file uploads and scheduled exports, and we add more sources as the proof of value or rollout grows.

Dashboards in tools like Power BI or inside your ERP are useful for fixed views, but they are static and often feel dated. They force everyone into one version of the numbers and, over time, only a few people remember how each report was built or what the fields mean. Beye focuses on the decision workflow. Business users ask a question and get a validated answer that pulls from multiple systems, checks against your rules and is ready to act on. Most customers keep their dashboards for reporting and add Beye as a conversational layer so questions turn into answers in minutes.

Copilot and generic AI chat tools are not built for data intensive workflows and do not understand your business rules. Beye is a specialized Generative BI workspace that models your data and KPIs to how the business actually runs, with a hands-on playbook for onboarding and change management. For a detailed comparison, see our Copilot alternative page.

Reliability is designed in from the start. We model your KPIs, business rules and vocabulary so Beye understands how your business works. For each question Beye breaks the problem into smaller steps, pulls data from the right sources and runs checks on joins, totals and time windows before showing an answer. It flags missing or unusual data and suggests next steps, and feedback from your users is built into the process so answers and coverage improve over time.

We start with one high impact business case, usually in operations, supply chain or finance. Together we define the decision you want to improve, the KPIs that matter and what a win looks like. Then we connect the right data sources, model them to your business and set up a workspace that is ready to use in about a week. Your team spends the rest of the proof of value asking real questions, getting answers and refining the setup with our help.

A typical proof of value runs for 8 weeks. The first part focuses on connecting data, capturing your business rules and getting the workspace live. The remaining weeks focus on real questions, regular use by your team and measuring impact on the chosen KPIs. By the end you have a working conversational workspace, saved views and a clear view of the time and cost you save so you can decide how to expand.

For an initial use case, subscription for a proof of value typically lands around ~$8k/month, depending on the complexity of the workflows and data. Pricing is evaluated case by case as you add more use cases, deeper modeling and higher data volume. Subscriptions are all in rather than per user and include a simple opt out period at the start.

Most teams begin with secure uploads and scheduled exports from their systems of record. We keep history and lineage so results are consistent and auditable, and we set refresh schedules that match how you run the business, whether that is daily, weekly or near real time for certain metrics. If you need additional connections, we scope them together during the proof of value.

You control what you send to Beye. Data is encrypted in transit and at rest, and access is limited by role and workspace. We are SOC 2 Type II on Google Cloud. If you work with PII we help you scope what should and should not be included. For more detail you can visit our Trust Center.

You keep the BI tools and reports that are working today. Power BI, spreadsheets and ERP reports remain the place for standardized reporting, audits and long-term history. Beye reuses the same KPI definitions where it makes sense and adds a conversational layer on top so business teams can move from question to validated answer in minutes. This reduces change risk and increases the value of the data stack you already pay for.

Start with a weekly or daily decision where delay is expensive and the current analytics process is painful. Good candidates are workflows that rely on multiple spreadsheets, ad hoc queries, Slack or email requests to a small group of experts, or reports that everyone waits days to receive. Examples include stockout recovery, fill rate and OTIF performance, margin and mix analysis or AR collections focus. We work with you to define success criteria and deliver a quick win before expanding.