Standard program
30-day POV
Free
Test one journey with your own cases and a pilot group. Includes setup, AI Workers, weekly reviews, and the final value assessment.
Sign up for a POVProof of Value program
Prove the value of service AI.
Test Circuitry.ai’s AI Workers on one service journey using your own cases, manuals, and policies. In 30 days, measure the change in accuracy, time, and cost, then decide where to deploy.
Free 30-day POV No production commitment
One service journeyScoped to your operation
Your experts and oursWeekly testing and feedback
A production decisionScorecard, ROI, and rollout plan
The 30-day program
From kickoff to a decision.
Plan for a few hours of expert time each week. We tailor the journey, users, and targets to your objectives. Readiness comes first. The 30 days start at kickoff.
Week 0 / Get ready
Agree on what success looks like.
Choose one journey and the decisions to test. Together we define the baseline, target, participants, and actions that require approval.
Circuitry.ai
Scope the journey, answer the security questionnaire, and document the access needed.
Your team
Name an executive sponsor, an IT owner, and expert users. Complete the POV agreement, NDA, and access approvals.
Milestone Scope and targets approved. Kickoff and weekly reviews booked.
Week 1 / Connect
Test the journey on familiar cases.
Bring 50–100 past cases with known outcomes. Your experts test whether an AI Worker can find the right source and reach a sound decision.
Circuitry.ai
Set up the POV environment, SSO, user roles, a shared issue tracker, and reporting. Load approved content and start with read-only connections to the CRM, ERP, field service, or ticketing systems in scope.
Your team
Share manuals, bulletins, and sample records. Have experts rate answers and flag missing evidence.
Milestone The journey runs end to end on the test set. Baselines and the pilot group are agreed.
Week 2 / Pilot
Put a small group to work.
Your pilot group uses AI Workers on real requests. Reviewers can inspect each recommendation and approve actions in your systems.
Circuitry.ai
Track decisions and handoffs, resolve knowledge gaps, and report accuracy and handling time against baseline.
Your team
Use the journey on live cases, review flagged answers, and record corrections in the shared tracker.
Milestone Accuracy reaches the agreed target, handoffs work, and sponsors clear critical issues before expansion.
Week 3 / Expand
See whether results hold at higher volume.
Extend the same journey to more users or channels in scope. Keep exceptions visible as the case mix changes.
Circuitry.ai
Tune routing and escalation. Report performance by user group and raise autonomy only where accuracy holds.
Your team
Invite the wider group, confirm which actions may proceed, and share volumes, staffing, and cost per request.
Milestone Sponsors review stable outcomes, remaining risks, and the agreed level of autonomy for each worker.
Week 4 / Prove
Decide where to go into production.
Compare pilot results with the baseline, review exceptions, and decide whether the journey is ready to scale.
Circuitry.ai
Deliver the before-and-after report, an ROI model based on your inputs, and a phased rollout and integration plan.
Your team
Collect user feedback, validate the findings, and review the business case with the executive sponsor.
Milestone A sponsor-reviewed scorecard, an agreed ROI case, and a go, refine, or stop decision.
Autonomous Service Journeys
A real workflow, on your data.
Choose one journey. Advisors answer from approved knowledge, Analysts measure performance, and Agents carry out authorized steps. Your team sets the handoffs.
Field service example
From a fault report to the right repair
Measure First-time fix rate and repeat truck rolls.
Request
A technician reports a recurring fault on a specific equipment model.
Decision
The Service Advisor retrieves the applicable bulletin, checks service history, and identifies a repair and compatible part.
Action and review
The Support Agent prepares the work order. A supervisor reviews conflicting evidence or a parts substitution before dispatch.
Technical support example
From a support request to a verified resolution
Measure Self-service resolution and average handling time.
Request
A customer describes an issue through the support channel in scope.
Decision
The Service Advisor checks model-specific instructions and recommends the next diagnostic step.
Action and review
The Support Agent records a confirmed resolution. If the issue persists, it hands the case and evidence to a specialist.
Warranty claims example
From a repair order to a coverage decision
Measure Expert agreement on coverage and time per claim.
Request
A dealer submits a repair order with the complaint, cause, and correction.
Decision
The Warranty Advisor checks policy terms and repair evidence. A scoring agent flags missing or conflicting information.
Action and review
An adjuster reviews exceptions and authorizes the next action under the agreed policy.
The outcome scorecard
What changed during the pilot?
Agree on the baseline and target before testing. Track results against a comparable set of cases, by channel and case mix, so your sponsor can judge the difference.
| Service outcome | Baseline at kickoff | Evidence during the POV |
|---|---|---|
| Self-service resolution | Share of eligible requests resolved without a human agent. | Count end-to-end resolutions and review reopened requests. |
| Average handling time | Minutes spent handling a comparable request, by channel. | Compare pilot and baseline minutes for the same request types. |
| Decision accuracy | Expert-rated correctness on a sample of past cases. | Review pilot answers and their evidence against the agreed rubric. |
| First-time resolution | Share of issues solved on the first contact or field visit. | Track first-contact or first-visit resolution using the same follow-up window. |
Use the measures that fit your journey. For field service, add correct-part dispatch and repeat visits. For warranty, add coverage accuracy and adjudication time.
Illustrative field service model
What would fewer repeat visits be worth?
For 40,000 work orders a year, Circuitry.ai’s Productivity, Outcomes, and Efficiency (POE) model puts the largest opportunity in avoiding repeat visits.
$2.57Mmodeled annual value
- Productivity $400K
- Outcomes $269K
- Efficiency $1.899M
See the assumptions and calculation
| Service measure | Baseline | Target | Confidence | Annual value |
|---|---|---|---|---|
| Diagnostic time | 28 min | 18 min | 80% | $400K |
| First-time fix | 68% | 82% | 70% | Tracked only¹ |
| Correct part dispatched | 78% | 94% | 70% | $269K |
| Truck rolls per work order | 1.40 | 1.05 | 70% | $1.764M |
| Parts return or restock rate | 18% | 8% | 75% | $135K |
Annual value = change per work order × annual volume × unit value × confidence. The modeled values total $2.568M before subscription cost. An illustrative $100K annual subscription (40,000 decisions × $2.50) gives about 26× gross value to subscription cost.
¹ First-time fix is a leading indicator. Its financial benefit is counted in avoided truck rolls. These figures are targets and assumptions from the example. Your POV replaces them with measured results and your costs.
For service and IT leaders
Set the boundaries before AI takes action.
During readiness, the service owner defines the decisions and IT approves the data, access, and review points. Add permissions in stages as the evidence supports them.
Knowledge and models
Ground answers in the right evidence.
Use retrieval-augmented generation to find the manual or policy for a specific model, region, and revision. Use rules for eligibility and approval limits, and predictive scores where historical data supports them. Experts check both the answer and its cited evidence.
Access and ownership
Review access before connecting.
Your organization owns its data. The readiness review covers data scope, dedicated AWS accounts, AES-256 encryption at rest, TLS in transit, and data export. Start with read-only access and grant each role only the permissions its work requires.
Autonomy and oversight
Set a human checkpoint for each action.
Start with recommendations or shadow tests against past decisions. Let an agent act on an approved request, route exceptions to the right reviewer, and record the evidence, decision, and override. Expand permissions when measured accuracy supports the change.
Evaluation and monitoring
Know when the workflow needs attention.
Keep a representative set of evaluation cases apart from tuning examples. Check source relevance, groundedness, and agreement with expert decisions. Monitor latency, escalations, and overrides as volume grows, and assign an owner to investigate regressions.
After the POV
Choose a path to production.
Your sponsor reviews the outcome report, ROI, and open issues. Move a proven journey into production, extend the pilot to answer a specific question, or stop.
Extended validation
90-day pilot
Monthly, by scope
Validate a broader workflow across more users, AI Workers, and integrated systems. Agree on the extra scope and fee before extending.
Enterprise rollout
Production
Per Service Decision Unit
Subscribe by completed decision, such as a claim, support case, or repair order. Agree on units, tiers, and support in the statement of work. Expand to additional regions, channels, and AI Workers in phases.
Start your proof of value
Which service decision would you like to improve?
Tell us where your team spends time, loses a day waiting for an answer, or sends someone back for a second visit. We’ll use that example to scope your POV.
- Choose the journey and outcome.
- Confirm the team, data, and approvals.
- Set the kickoff date.
