Move from embedded AI assistants to production workflows with client-specific architecture, integrations, data boundaries, and deployment controls. Halley AI helps teams design and launch practical AI systems connected to trusted content, approved data sources, and operational handoffs — without treating compliance-sensitive workflows as generic chatbot deployments.
Standard assistants answer common questions and qualify basic requests. Custom implementation is for workflows that need controlled data access, system actions, auditability, secure handoffs, or industry-specific operating rules.
Map users, data sources, approvals, escalation points, and handoffs before building the assistant.
Connect approved files, FAQs, records, and systems with clear rules for what the assistant can retrieve.
Add calculators, lookups, schedulers, ticket creation, CRM handoffs, or other domain-specific actions.
Collect required context, validate fields, reduce low-quality submissions, and route work to the right team.
Turn repeated questions, content gaps, and intake patterns into better reporting and decision support.
Design around least privilege, logging, retention, model boundaries, and human escalation requirements.
We identify the workflow, users, source systems, risk boundaries, success metrics, and the data that should be explicitly out of scope.
We define prompts, tools, data-access patterns, integration points, retention needs, human handoffs, and operating controls before buildout.
We implement the assistant, analytics workflow, or intake flow and test it against real questions, edge cases, expected handoffs, and failure modes.
We monitor usage patterns, content gaps, and escalation quality so the implementation improves with operational evidence, not guesswork.
Healthcare organizations often need a stricter implementation model than a public website assistant. Halley AI can support HIPAA-sensitive workflows through a scoped custom deployment path when PHI is in scope.
Important: Public demos, marketing assistants, and standard lead-capture forms are not intended to collect PHI. PHI workflows require a defined implementation scope, approved vendors and subprocessors, appropriate agreements, and documented safeguards before launch.
When PHI is in scope, the deployment plan must account for business associate agreements and approved subprocessor paths.
Define exactly what PHI the assistant may access, what it must refuse, and when a human or secure system should take over.
Plan logging, review, retention, deletion, and incident response expectations before handling regulated workflows.
This is why we describe healthcare work as HIPAA-capable custom implementation rather than blanket HIPAA compliance for every Halley AI deployment.
Proof in practice: Health Plan Alliance deployed a single-tenant Knowledge Query Platform that turns processed documents, tables, summaries, and metadata into grounded answers with citations — while keeping vector storage under client-controlled infrastructure.
Workflow map, architecture notes, source inventory, escalation design, and launch criteria.
Assistant instructions, validation rules, tool contracts, refusal rules, and test scenarios.
Deployment checklist, monitoring plan, owner handoff, and iteration schedule after launch.
A guided path from demo to production — architecture, data boundaries, and handoffs designed around your workflow.