Business AI Transformation

DataWise takes a whole operation, scattered across tools, spreadsheets, and people’s heads, and centralizes it into one work-OS with AI built on top. For a live-performance company we scoped every workflow, centralized operations into a monday.com-based work-OS delivered in waves, and the system is live and in daily production use today. Transformation here means a working operation, not a strategy document. Read the full story in our operations-transformation case study.

What does an AI transformation with DataWise actually include?#

It starts with scoping every workflow in the business, not the ones that look digital, all of them. In our flagship engagement for a live-performance company, that meant the command-center dashboard, daily and weekly operations, attendance, rentals, suppliers, receipts, venues, and production calendars, all centralized into one monday.com-based work-OS with integrations, automations, and observability built in. The platform itself is a choice we make per client, not a commitment we arrive with: DataWise is platform-agnostic, and monday.com earned its place in that engagement because it fit the company’s people and workflows. Delivery ran in waves, so the team absorbed each layer while working, and the result is not a recommendation deck: it is the system the company runs on every day.

Where does the AI come in?#

In two honest layers. The first is already delivering: automations and integrations that remove manual steps, and observability that shows the operation in one place instead of N tools. The second is the roadmap we design on top of a centralized operation: agents, continuous learning, proactive insights, and assistants working over the operation’s own data. We present that second layer as vision, not as a delivered outcome, because that is the truthful state, and because the order matters: AI agents over a scattered operation automate chaos. Centralize first, then let the AI layer compound. This sequencing is also the documented failure point industry-wide: tools that do not integrate with core systems are a leading, repeatedly-cited barrier for Israeli AI buyers (Calcalist/CTech coverage of the KPMG-Microsoft Israel survey), alongside employee skills and security, and data readiness is the real blocker in most stalled initiatives. The wave is neither hypothetical nor foreign to Israel: business AI use here reached about 28% of firms in 2025 and keeps climbing, per CBS data via the Israel Democracy Institute, and it is reaching traditional industry, food-and-beverage maker Strauss Group began rolling out 1,000 AI-copilot licenses in 2025, per Calcalist.

Does DataWise practice what it sells?#

Yes, verifiably. DataWise built a full production web platform, cloud-native on Kubernetes/EKS, a multi-panel product with search, quoting, CRM, and analytics, using an agentic AI development methodology end to end: architecture decision records, automated verification, and AI-driven engineering workflows. We also built a voice AI agent that ingests a website’s content via its sitemap, builds product knowledge automatically, and holds spoken conversations that qualify and convert visitors into leads, and a WhatsApp operations agent that delivers an organization’s materials in-chat in Hebrew voice and text. The methodology we bring to your operation is the one we run our own engineering on.

What we are, and what we are not#

• We are: the same senior people scoping the operation and building the system, no handover between a strategy team and a delivery team.
• We are: platform-agnostic; the work-OS is chosen to fit your people, and you own what we build.
• We are: wave-based; the operation keeps running while it transforms, with production use as the finish line.
• We are not: a transformation-program vendor selling a phased slide deck.
• We are not: staff augmentation, and not a chatbot shop.
• We are honest about readiness: if the diagnosis says your data or workflows are not ready for the AI layer yet, that is what you will hear, with the order of work to get there.