AI Consulting Services
Client-facing AI systems built for measurable business outcomes
Explore completed implementation patterns across lead operations, support performance, project execution, lifecycle nurture, and custom-built workflows tailored to your business.
Lead Intake System
Unified capture, qualification, routing, and conversion visibility.
- Outcome: faster first response + better qualification consistency.
- Control: SLA breach alerts and routing guardrails.
Stage Conversion
SLA Bands
Booked Trend
Regional Pipeline Map
Recommended AI Action
Prioritize web leads with response-time risk > 90 minutes and auto-create callback tasks for top-fit accounts.
Support Triage System
Prioritization, escalation discipline, and SLA protection at scale.
- Outcome: improved FCR and lower backlog volatility.
- Control: severity model + closure QA standards.
Severity Mix
Root Cause Mix
Resolution Channel
SLA Risk Curve
Queue by Team
Aging Distribution
Recommended AI Action
Auto-escalate high-risk tickets predicted to miss SLA and trigger proactive customer update workflows.
Project Delivery System
Milestone governance, dependency visibility, and launch confidence.
- Outcome: fewer late-cycle surprises, stronger launch reliability.
- Control: milestone health + risk thresholds.
Delivery Velocity Timeline
Defect Burndown
Scope Change Trend
Milestone Status
Load by Workstream
Risk Mix
Blocker Trend
Recommended AI Action
Detect milestone drift early and auto-generate dependency mitigation plans for critical path items.
Email & Nurture System
Segment strategy, AI-assisted messaging, and conversion analytics.
- Outcome: stronger replies and nurture-to-meeting yield.
- Control: frequency capping + deliverability hygiene.
Nurture Funnel
Segment Lift
Send-Time Curve
CTA Variant Wins
Outcome Mix
Throughput
Reply Velocity
Recommended AI Action
Boost warm-segment reply rates with adaptive subject line generation and send-time optimization.
Custom Systems (Anything You Need)
If your workflow doesn’t fit a template, we design and implement a tailored AI-enabled operating system around your exact process.
- Outcome: a system shaped to your exact business reality, not a forced template.
- Control: architecture decisions documented with explicit tradeoffs and rollback paths.
Workflow Throughput
Queue by Stream
Exception Trend
SLA Bands
Automation Mix
Owner Load
Change Requests
Recommended AI Action
Identify top exception drivers and auto-propose automation candidates ranked by effort vs impact.
Typical delivery timeline
A structured 4–8 week engagement with explicit deliverables, decisions, and go-live controls.
Discovery & Baseline
- Stakeholder interviews + workflow mapping
- Current-state KPI baseline and pain-point heatmap
- Data/source inventory and access plan
- Risk register (operational + technical)
- Deliverables: Discovery brief, KPI baseline, draft scope boundaries
- Gate: Discovery signoff + target outcomes approved
Architecture & Design
- Future-state process + owner responsibilities
- Rules engine/routing logic and exception handling design
- Dashboard wireframes + reporting definitions
- Acceptance criteria mapped to business outcomes
- Deliverables: Solution blueprint, data contract, test strategy v1
- Gate: Design review and implementation approval
Build Iteration 1
- Core workflow implementation + instrumentation
- Initial automations and SLA controls
- Operator dashboard v1 + alerting logic
- Integration shakedown (inputs/outputs)
- Deliverables: Working prototype, test evidence pack v1
- Gate: Midpoint demo + go/no-go to iterate
Build Iteration 2 + QA
- Exception-path hardening and edge-case coverage
- Performance + reliability checks under expected load
- Data reconciliation and metric parity validation
- Runbook drafting + handoff prep
- Deliverables: QA report, release candidate, operational runbook
- Gate: Acceptance test pass + launch readiness signoff
Launch, Enablement & Stabilization
- Production rollout with rollback protocol
- Operator + leadership enablement sessions
- Daily hypercare metrics during stabilization window
- Optimization backlog prioritized by ROI
- Deliverables: Final dashboard package, handoff set, 30-day optimization plan
- Gate: Transition to operating cadence
Governance and quality standards
Execution discipline that protects quality, ensures traceability, and keeps ownership clear after go-live.
Quality Assurance Framework
- Functional: primary path + exception path validation against requirements
- Data: field-level integrity checks, reconciliation, and null/format controls
- Reliability: retry/fallback behavior, timeout handling, alert thresholds
- Usability: operator workflow clarity, friction review, and error messaging quality
- Security hygiene: role-based access assumptions, sensitive field handling, audit notes
Acceptance Criteria Model
- Every objective tied to a measurable KPI with baseline and target range
- Pass/fail evidence captured per milestone (screens, logs, metric snapshots)
- Formal signoff sequence: business owner + operational owner
- Known limitations and deferred items documented with owner + due window
- Production readiness checklist required before launch authorization
Operating Model & Ownership
- Defined owners for triage, change requests, and incident escalation
- Weekly operator review cadence + monthly leadership KPI review
- Runbooks for normal operations, exceptions, and rollback scenarios
- Change protocol: intake → impact review → test → approve → release
- Continuous improvement queue prioritized by business impact and effort
Risk, Compliance & Auditability
- Decision log for significant workflow/routing logic changes
- Traceability from requirement → implementation → test evidence
- Policy checkpoints for regulated or customer-sensitive operations
- Escalation matrix with response SLAs for critical incidents
- Post-incident review template with corrective/preventive action tracking
Ready to build your first AI system?
Start with one workflow. We’ll implement it with measurable outcomes and a clean handoff your team can run.
Fast response + recommended first sprint.