Advisory & Assessment
- Opportunity assessment and workflow mapping
- Use-case prioritization by value and feasibility
- A written roadmap your team or ours can execute
- No commitment to a specific tool or vendor
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HOW WE WORK
A disciplined path from AI interest to a system your team actually runs.
The methodology below applies whether the engagement is a focused pilot or a multi-department rollout. What changes with scale is governance, phasing, and how many stakeholders need to sign off — not the discipline.
ENGAGEMENT MODELS
Start where it makes sense for your organization.
Not every organization is ready for the same starting point. These are the three shapes an engagement typically takes.
Pilot / Proof of Concept
- Scoped to one real workflow with defined success criteria
- Built against production data and edge cases, not a demo
- A clear go / no-go decision before further investment
- Typically the fastest path to a defensible business case
Implementation & Scale
- Full integration build-out, testing, and documentation
- Governance, approvals, and monitoring for production use
- Phased rollout across teams, locations, or departments
- Ongoing optimization based on real usage
METHODOLOGY
Discover. Design. Build & Integrate. Rollout. Optimize.
Five phases, applied with the same rigor whether the scope is one workflow or a company-wide rollout.
Discover
We map the current workflow end to end: triggers, systems, data, volume, exceptions, and who is accountable today. Assessment is not limited to what the tool can do — it includes what the organization is actually ready to change.
Design
We define the architecture: which steps use AI, which use deterministic rules, which integrations are required, and where human approval sits. Design decisions are documented so they can be reviewed before anything is built.
Build & Integrate
We implement against realistic and adversarial test cases, not just the happy path. Integrations are built with least-privilege access, and error handling is treated as a first-class requirement, not an afterthought.
Rollout
For larger organizations, rollout is phased: a pilot team or location first, then a defined expansion plan with stakeholder sign-off at each stage. We document the operating procedure so your team can run the system without us.
Optimize
We review exceptions, measure the outcome against the criteria defined before launch, and adjust. Production AI systems change as data, vendors, and business needs change — optimization is ongoing, not a one-time handoff.
HOW A WORKFLOW ACTUALLY OPERATES
AI and automation working alongside the systems you already run.
A production workflow reads from and writes to your existing systems, applies rules and AI where each is the better tool, keeps a human in the loop where the decision warrants it, and reports back so the result can be measured.
GOVERNANCE FOR LARGER ROLLOUTS
Scale changes the process, not the standards.
Stakeholder alignment
Before a phase expands, the teams affected by it — operations, IT, legal, and the people who will use the system daily — review what changed and what to expect.
Security & legal review
We support your security questionnaire, data processing agreement, and procurement process rather than asking your organization to bypass it. Details in our security approach.
Change management
Documentation, training material, and a defined escalation path so the team using the system day to day is not surprised by how it behaves.
TECHNOLOGY APPROACH
Model-agnostic by default.
We evaluate AI models and vendors against the requirements of the workflow — reliability, data handling terms, security posture, cost, and how easily the organization could change providers later — not just capability. Implementations commonly connect to systems such as Salesforce, HubSpot, Pipedrive, ServiceTitan, Google Workspace, Microsoft 365, Twilio, and automation platforms like Zapier, Make, and n8n, alongside model providers such as OpenAI, Anthropic, and Azure OpenAI, depending on what your organization already runs and approves.
Where feasible, a workflow can be deployed inside your own cloud environment, tenant, or approved integration platform instead of a separate DataVine-hosted system, and we document every third-party dependency so it can be reviewed like any other vendor in your stack.
QUESTIONS FROM LARGER ORGANIZATIONS
What procurement, security, and operations teams usually ask.
Can you work within our procurement and security review process?
Yes. We can complete vendor or security questionnaires, execute NDAs and data processing agreements before sensitive information is shared, and adapt our process to your existing review and approval requirements rather than asking you to work around them. See our security and data handling approach for detail.
How do you handle rollouts across multiple departments or locations?
We default to a phased approach: a single team, process, or location first, with defined success criteria, before expanding. Each phase includes a stakeholder checkpoint so leadership can decide whether and how to scale, rather than committing the whole organization to an unproven workflow at once.
Do we need to use a specific AI vendor or model?
No. We are not tied to one provider. Where you already have an approved vendor list, existing model relationships, or a preferred cloud environment, we design around those constraints rather than introducing new ones.
What if we already have an internal data, IT, or AI team?
We can work alongside an internal team in an advisory capacity, take primary responsibility for a defined workstream, or hand off a completed implementation with documentation so your team can operate and extend it independently. The right model depends on your team's capacity and the scope of the project.
Who is our point of contact during a larger engagement?
Every engagement has a defined owner responsible for scope, status, and escalation, with a regular reporting cadence appropriate to the size of the project. For multi-phase work, that includes a checkpoint with stakeholders at the end of each phase before proceeding to the next.
READY TO SCOPE AN ENGAGEMENT?
Tell us the size and shape of the problem.
Whether it's a single workflow or a rollout across departments, we'll recommend the engagement model that fits — including when the right answer is to start smaller than you expected.