Complex organizations
Build a validated pipeline of several Agent opportunities across systems, data, and business priorities.
Enterprise services
Data & Architectural Discovery
A deep evaluation of your data landscape and systems architecture to identify, validate, and prioritize the highest-value Agent opportunities SUPERWISE can build.
Deliverable preview
Expected outcome
A formal, prioritized roadmap for which business processes to give to AI agents with cost/ROI model where possible.
- Architecture fit and data-readiness report
- Prioritized agents and value proposition
- Alignment to business priorities and future agent work
- For
- Complex organizations · Cross-functional teams
- Takes
- On request
- Costs
- On request
- You get
- Architecture fit and data-readiness report
Short answer
AI integration services grounded in your systems
SUPERWISE® AI integration services help organizations evaluate their data landscape, systems architecture, and candidate workflows before committing to an AI build.
Your team leaves with a prioritized opportunity roadmap, an architecture blueprint, and a build sequencing plan.
Who it is for
Choose the path that matches your team
Cross-functional teams
Bring business units together to identify workflows, test feasibility, and agree on sequencing.
Deliverables
AI integration services grounded in your systems
Guided discovery
A series of envisioning workshops targeted at uncovering the business processes that would yield the biggest benefit from AI agents.
- Review / document supporting systems architecture
- Discover data and data-quality aspects
- Value prioritization of potential efforts
Expected outcome
A formal, prioritized roadmap for which business processes to give to AI agents with cost/ROI model where possible.
- Architecture fit and data-readiness report
- Prioritized agents and value proposition
- Alignment to business priorities and future agent work
The engagement
How it works
What's involved in the discovery
Systems & data mapping
- Inventory core systems, integrations, and data stores
- Identify accessible vs. locked or legacy data sources
Use case discovery workshops
- Cross-functional workshops across business units
- Build a candidate workflow long-list: volume, complexity, value
Technical Feasibility
- Data readiness and integration feasibility per candidate
- Architecture fit: purpose-built vs. frontier vs. hybrid Agent
Value & Prioritization
- Value/effort/risk scoring across candidates
- Recommended sequencing across a multi-Agent roadmap
Proof of Concept (optional)
- Rapid prototype of one flagship use case
- “Art of the possible” for stakeholders
Deliverable & Readout
- Prioritized Agent opportunity roadmap
- Architecture blueprint and build sequencing plan
Proof
See governed AI in practice
Customers with published work across healthcare, manufacturing, and governed AI operations.
What it puts to work
The products behind Data & Architectural Discovery
The SUPERWISE platform
Discovery maps which data and systems your agents can use safely on the platform.
AI integration services questions
What to expect before you start
The discovery maps core systems, integrations, data stores, and candidate workflows. It then evaluates data readiness, technical feasibility, value, effort, and risk.
The work uses cross-functional workshops and a review of your systems, integrations, and data sources. Business and technical stakeholders help identify workflows and business priorities.
You receive a prioritized AI agent opportunity roadmap, an architecture blueprint, and a build sequencing plan. A proof of concept for one flagship use case is optional.
The prioritized roadmap and architecture blueprint provide the input for an AI agent development engagement focused on the selected workflow.
Related reading
All questions- When people say "AI," what are they talking about?At least six different technologies, with different costs, risks, and rules. Three independent questions sort them: did a person write the rule or did a machine learn it, does it…
- Is it predicting something, or making something?Predictive AI scores something that already exists, and the real answer eventually arrives to check it against. Generative AI produces something new, where there is usually no answer to check.
Next step
Talk to us about Data & Architectural Discovery
Best suited for complex organizations needing a validated pipeline of several Agent opportunities.