The AI-first business design framework
Strategy & outcomes. Define the business goals, constraints, and approved AI use cases.
Data & integration. Map sources, cleanliness, access, and privacy controls.
Workflows & agents. Redesign tasks into automated flows with human-in-the-loop checkpoints.
Guardrails & policy. Approvals, refusal rules, logging, and audit trails baked in.
Measurement. Instrument success metrics, SLAs, and cost controls.
Change & enablement. Training, adoption plans, and owner assignment.
Why it matters now
- Cost curves: AI ops get cheaper/faster, rewarding early operating-model shifts.
- Data moats: Early instrumentation builds better retrieval, evals, and reinforcement.
- Talent leverage: Teams that work with AI-first processes ship more with fewer errors.
- Risk posture: Guardrails-first organizations avoid breaches, hallucinations, and brand hits.
How Zyphh implements this
- 2–3 hour discovery on strategy, risks, and data.
- Map processes → target AI-first workflows with approval points.
- Prototype key flows with guardrails, evals, and observability.
- Launch pilots in 2–4 weeks; measure ROI and adoption.
- Expand to a roadmap with owners, playbooks, and governance.
AI-first design is not a chatbot; it’s a full operating model with data, guardrails, and measurement.
FAQ
How long?
Pilots in 2–4 weeks, full roadmap in 30–45 days.
Who owns it?
We set accountable owners per workflow with clear SLAs and dashboards.
Can we start small?
Yes—begin with 1–2 workflows to prove ROI and safety, then scale.
Regulated industries?
We deploy approvals, redaction, logging, and policy prompts aligned to your controls.