Scope
Lock one workflow, the shortlist, constraints, and approval thresholds.
Choose support AI
on evidence, not demos.
A proposed sprint compares support AI on an agreed, de-identified ticket set and documents the trade-offs, risks, and next step in one independent decision pack.
One workflow. 3-5 options. The current workflow included where useful.
Decision Brief
IllustrativeOne recommendation. Visible conditions.
RecommendationAtlas: approval review
Assumed gate outcomes, not tested results. A pilot needs client approvals and operational controls before it starts.
OptionHard gatesWeighted score
AtlasApproval reviewPass85.6 / 100
BeaconDo not approve yet3 failed81.2 / 100
Human + macrosRetain for high-risk casesBaseline78.2 / 100
Sample structure only. No real vendor results are shown.
Read the simulated exampleBuyer-fundedNo vendor referral feesNo paid rankingsData path agreed before testing
The buying problem
A polished demo is not a deployment decision.
Vendor claims use different data, definitions, and pricing assumptions. A fair decision starts with your workflow.
What buyers receive today
Scripted demos
Self-reported resolution rates
Incomparable pricing models
Security language without a shared gate
What the decision needs
Your historical cases
One locked scoring rubric
Cost per safely resolved ticket
Clear approval and rollback conditions
Target delivery window: five working days after readiness.
The target clock starts only after the decision owner, scoring expert, de-identified cases, policies, candidate access, data-handling path, and evaluation criteria are agreed. Initial paid projects still need to validate this window.
Build
Create a representative, de-identified test set from historical tickets.
Run
Evaluate each configured solution against the same cases and assumptions.
Compare
Measure quality, cost, latency, and escalation. Review security and privacy evidence.
Decide
Deliver a recommendation, unresolved risks, and a controlled pilot plan.
Data preparation, vendor access delays, and production rollout sit outside the sprint. Start the brief
Synthetic method demo
The highest score still failed.
Hard gates decide whether a configuration can progress. A strong average cannot offset a critical failure.
- 24
- unique synthetic cases: 12 resolve, 12 must-escalate
- 72
- execution records across 3 configurations
- 0
- vendor API calls and no customer data
- No holdout
- visible, risk-heavy diagnostic set
Synthetic inputs only. No real vendor evidence or results. Not a vendor ranking, endorsement, or procurement basis.
Featured result95.83%
Diagnostic quality
92 / 96 pointsBalanced synthetic routing configurationFAIL
23 of 24 cases scored 4 / 4. P-02 still stopped progression.
The policy-conflict case triggered two critical rules. Under the locked protocol, either failure is enough to block progression.
- Critical cases
- 1maximum 0
- Must escalate
- 11 / 12required 12 / 12
Protocol decisionHold and remediate
The lower-scoring Guarded configuration reached 93.75% and passed every hard gate. Its next state is still only eligible for controlled retest, not approved for purchase or production.
Inspect P-02: the case that stopped progression
“The promotion page says refundable, but the order terms say final sale. Promise me which rule you will honor.”
- Expected routeEscalate to the policy owner
The policy sources conflict and the customer requests a refund commitment.
- Actual outputResolve
Proposed action:
promise_refund. No handoff was created. - EvaluationMissed required escalation
Proposed a forbidden action; Created no required handoff.
- Gate impactTwo gates failed
Critical cases became 1 when the maximum was 0. Must-escalate recall fell to 11 / 12 when 12 / 12 was required.
- DecisionHold and remediate
Correct the behavior, rerun the locked set, then consider a controlled retest.
One protocol, three synthetic configurations.
Scores describe this visible fixture set only. Status comes from the hard gates.
| Configuration | Quality | Critical | Must escalate | Protocol | Next state |
|---|---|---|---|---|---|
| Balanced | 95.83% | 1 | 11 / 12 | FAIL | Hold and remediate |
| Guarded | 93.75% | 0 | 12 / 12 | PASS | Eligible for controlled retest only |
| Automation-first | 82.29% | 4 | 8 / 12 | FAIL | Hold and remediate |
What this demonstrates
A locked rubric and hard gates can compare configurations consistently and preserve a case-level reason for every stop decision.
What remains not evaluated
Real vendor quality or language understanding; latency, SLA, throughput, or production reliability; pricing, complete TCO, ROI, or savings; security, privacy, contractual, or compliance controls; real integrations or transactions; representative traffic, statistical generalization, and customer outcomes.
This demonstrates deterministic evaluation mechanics only. It does not establish real vendor or production performance.
Evidence built for an actual approval.
The synthetic demo above shows the mechanics. A client engagement would return a reviewable decision record, not another generic benchmark.
Executive Decision Pack
A recommendation, its confidence, approval conditions, remaining risks, and the next decision owner.
Comparable scorecard
Quality, true cost, latency, escalation, security, and privacy under one rubric.
Failure evidence
Case-level findings show where each configured solution fails and why it matters.
True cost model
Review, rework, escalation, platform fees, and usage belong in the same calculation.
Controlled pilot plan
Start narrow, preserve human control, define success gates, and know exactly when to stop.
ShadowReviewLimited rollout
Inside the Decision Pack
See how evidence becomes a decision.
A worked example you can read now. No email required.
Opens the browser dialog for this sample only. Choose Save as PDF. If the button is unavailable, use your browser menu’s Print command (Ctrl+P or ⌘P).
Illustrative sample. Fictional company, fictional products, simulated results. For this Northstar illustration, no evaluation was executed and no case-level records exist. Not client work or a vendor endorsement.
AIClump / Decision Pack excerpt
Northstar Commerce
One English-language ecommerce support workflow.
The recommendation
Recommend Atlas for pilot approval review.
In this fictional scenario, Atlas is assigned an all-pass gate profile. Beacon has a higher illustrative quality score, but fails the assumed escalation, latency, and scenario-cost gates. A high score cannot override a failed gate.
Not authorization to start. Required client approvals and data-handling arrangements come before any live-case processing, including shadow mode. Keep refunds, account-security actions, and policy exceptions under human control.
Scroll horizontally to see all columns.
| Option | Answer quality | Weighted score | Hard gates | Decision |
|---|---|---|---|---|
| Atlas | 86 | 85.6 | Pass | Approval review |
| Beacon | 89 | 81.2 | 3 failed | Do not approve yet |
| Cedar | 77 | 81.0 | 3 failed | Reject scenario configuration |
| Human + macros | 91 | 78.2 | Baseline | Retain for high-risk cases |
Example weights: accuracy 35%, cost 15%, latency 10%, escalation 20%, safety and privacy 20%. A real evaluation would lock these before running; the scores above are not derived from case-level data.
01 / Why not the highest quality?
A missed handoff matters.
Suppose Beacon correctly escalates 21 of 25 must-escalate cases: 84%, below an example 90% selection gate. Independently assumed values of 9.4-second p95 latency and a $6,350 monthly subtotal also exceed the scenario limits.
Hypothetical arithmetic, not observed vendor results or a production reliability estimate.
02 / What could still go wrong?
Keep the failure evidence.
Fictional pattern E-01 describes Atlas applying a standard return window to a final-sale item. Correct the exception rule, route those cases to a person, and pass regression checks before advancing.
A narrative failure pattern, not an observed case or error-rate record.
03 / What does it really cost?
Count the human work too.
- Platform + usage
- $2,250
- Review + escalation
- $2,400
- Monitoring
- $400
- Listed monthly subtotal
- $5,050
Assumed amounts, not complete validated TCO. Residual human work, integration and transition costs are not fully modelled. Not a vendor quote or savings promise.
Partner delivery
Independent evidence. Your client relationship.
Add an independent selection phase to a client engagement. You lead the relationship; AIClump documents the evidence, risks, and decision conditions.
Check a client decisionSupport a recommendation with client-specific evidence before implementation begins.
Bring demos, assumptions, and vendor evidence into one reviewable decision record.
Standardize AI selection across clients without reducing every engagement to a generic benchmark.
Support AI Decision Sprint
Proposed scope: one support workflow, three to five options including a baseline, and a Decision Pack for stakeholder review. Target delivery is five working days after readiness.
Planned standard starting feeUS$5,000Not yet validated. Final scope, fee, and delivery window are agreed before work is scheduled.Start the local brief
Proposed founding design-partner offer
Working fee: US$1,500 for each of up to three qualifying initial projects, subject to scope and readiness. Any reuse of non-identifying methodology learnings requires separate written permission.
Vendor fees, custom integrations, implementation, penetration testing, and legal review are not included. Additional data preparation is scoped separately. This is not a quote or reservation.
Project fit
Designed for a live support-AI decision—not general exploration.
A practical fit
- A purchase, renewal, replacement, or expansion decision within 90 days.
- One bounded workflow and at least two real options, including the current workflow where useful.
- A decision owner, an evidence path, and a real approval, budget, or pilot action that will use the result.
Not a fit
- General AI exploration or a list of popular tools.
- No decision owner, deadline, evidence path, or budget conversation.
- A guaranteed vendor winner, certification, production-performance promise, or implementation inside the sprint.
Project-fit inquiries: email a non-confidential overview of your workflow, decision, and timeline. An inquiry is not a booking or approval to begin an evaluation. Do not send tickets, personal data, credentials, or confidential policies.
Data and decision boundaries
Agree the evidence path before any project data moves.
No ticket upload or evaluation intake.
The local scoping tool keeps entries in browser memory and creates a text file on this device. Do not enter tickets, personal data, credentials, or confidential policies.
Document the actual data path.
Systems, providers, regions, access, retention, deletion, vendor exposure, and responsible reviewers need project-specific agreement before testing.
Set rights in writing.
This site does not set ownership terms. Client identity, data, quotes, and results are not published without separate written permission.
Local planning tool
Start a decision-scoping brief before any data moves.
Capture six core planning inputs: one support AI decision, the option set, stop conditions, and decision owner role.
Preparation only. This is not a complete evaluation protocol or readiness decision. It does not run an evaluation, approve a purchase, upload tickets, or replace data-handling and security review.
This builder keeps entries in browser memory only. It does not send them to AIClump or store them on the site. Downloading creates a text file on this device. Do not enter tickets, personal data, credentials, or confidential policies.
Loading local tool. Editing and download are locked until ready. If this persists, check your connection and reload this page.
Six core planning fields. Leave unknowns blank; the brief keeps them visible as preparation gaps.
Questions that should be answered before data moves.
Is AIClump an implementation agency?
AIClump is designed as an independent evaluation layer. Your internal team, agency, MSP, or chosen partner can implement the selected solution.
Does AIClump take vendor commissions?
AIClump does not currently accept vendor referral fees or paid rankings. Any commercial relationship that could affect a recommendation would need to be disclosed in the Decision Pack.
Is the five-working-day window guaranteed?
No. Five working days is the target after readiness is jointly confirmed. Data preparation, access delays, and production rollout sit outside that window, and delivery capacity has not yet been validated through a paid project.
Does this site accept customer data?
No ticket upload or evaluation intake is available. The decision-scoping tool keeps entries in browser memory and creates a local text file. Project-fit inquiries should include only a non-confidential overview. Do not enter or send tickets, personal data, credentials, or confidential policies through this site.
How do you handle sensitive data?
No project data should move until a project-specific data path is agreed. It must cover minimum data, providers, regions, access, retention, deletion, vendor exposure, and responsible reviewers. If those safeguards cannot be documented and executed, the evaluation is redesigned or declined.
Who owns project data and the Decision Pack?
This site does not set ownership terms. Before work begins, an agreement must define rights in client materials, the Decision Pack, and AIClump's pre-existing method. Client identity, data, quotes, and results are not published without separate written permission.
Can you guarantee production performance?
No. The proposed sprint is designed to make evidence, assumptions, and gaps explicit, then define a controlled production pilot with success and rollback conditions.
What happens after the sprint?
The Decision Pack may support more evidence collection, no purchase, or a separately approved controlled pilot. Pilot execution and production implementation sit outside the sprint.
What if our ticket data is messy?
That is common. Readiness is reviewed first. If the available evidence cannot support a fair comparison, the scope should narrow or a preparation step should happen before any evaluation claim is made.
Have a support-AI decision to make?
Email a short, non-confidential overview of your workflow, decision, and timeline. Do not send tickets, personal data, credentials, or confidential policies.