Data + AI readiness session
An assessment of the current environment against the AI use cases on the table, for organizations with AI plans and data still spread across ERP, CRM, documents and spreadsheets.
What the session assesses
Seven areas, each read against the AI use cases the organization wants in production, so each finding ties back to the use cases it affects.
The path the assessment follows, from the source systems to the AI use cases.
- Data
- Where the data each use case needs sits today, and how complete and current it is.
- Architecture
- How data moves from the source systems today, and the data foundation the use cases would run on.
- Governance
- Business definitions, ownership, access policies and lineage, so teams and AI work from the same numbers.
- AI
- The value each use case targets, the data it depends on, and how its accuracy would be measured before it scales.
- Security
- What an agent would be allowed to read, under whose permissions, and how sensitive fields are masked.
- Integration
- How data comes in from the source systems, and how answers and actions would reach the ERP, the CRM and the other applications people work in.
- Operational readiness
- Who would run each use case after go-live, the skills on the team, and the approvals and monitoring a use case in production needs.
Deliverables
The session delivers a practical picture of the environment today and the order in which to close the gaps.
Current-state assessment
A scored review of the environment across the seven areas, use case by use case.
Key technical and operational gaps
Each gap comes with the effort to close it and the use cases waiting on it.
Data foundation architecture considerations
The target state the use cases depend on: how data comes in, where it is modeled on Snowflake, and how teams and agents share the same business definitions.
AI opportunities tied to the environment
Use cases ranked by value and by what the data supports today, each marked ready to build or waiting on a gap.
Recommended priorities
The order to work in, starting with a process someone can already put a number on (hours a week, an error rate, days added to the close), with the KPIs to track.
Practical next steps
The concrete actions that follow, in order, up to the first use case worth building.
How the session runs
Who takes part
From the organization, a sponsor who owns the priorities and the people who know the data and the processes. From Viewnear, the data and AI architects who would scope and build the work.
What the organization brings
The AI use cases under consideration, a walkthrough of the source systems and the current architecture, and time with the people who run the processes.
Working sessions
Working sessions with the business and technical owners go through the seven areas and test each use case against the data it needs.
Readout
A readout with the sponsor and the stakeholders walks through the findings and the recommended priorities.
What usually comes next
Depending on what the session finds, the work usually continues in one of two ways.
- How the advisory works
Data + AI advisory
When the business needs a costed plan before it builds, advisory turns the findings into use cases ranked by value, the KPIs to track and an architecture blueprint.
- How a full program runs
Full transformation
When the data foundation and the agents both need to be built, a full transformation builds the foundation first, then takes the agents into daily operations.
Real-time insight into 20,000+ students, live in seven weeks
Education · Miami & LATAM
A group of universities had academic records and LMS learning events in separate systems, updated in batches. Viewnear built a real-time student data pipeline on Snowflake, with access roles, network policies and lineage designed in from the first table, so academic and learning-activity data now sit in a single source.
- Students across Miami & LATAM
- 20k+
- Caliper learning events, was batch
- Real-time
- Core sources unified (Blackboard + Caliper)
- 2
- To a governed, real-time foundation
- 7 weeks
Request a readiness session
A short note on the AI use cases under consideration and where the data sits today is enough to start. An architect replies within one business day.
Prefer email? contact@viewnear.com