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Grok Bot+18 agentsAI Vendor Matchmaker — Compare AI Providers
Turn your AI buying needs into a requirements matrix, evidence-based shortlist, TCO comparison, and practical proof-of-concept plan.
$9.99
AI Vendor Matchmaker — Compare AI Providers
Example session with this skill installed
We need an AI provider for a customer-support triage pilot. Compare these three candidates from the notes I provide. Ask only for missing inputs that could change the choice, separate mandatory gates from preferences, normalize the offers, and design a 3-week POC with measurable acceptance criteria. Do not research or assume current features or pricing; mark unsupported facts unknown.
- Read your context and instructions
- Compiled the ai vendor matchmaker
Executive recommendation
Decision status: INSUFFICIENT EVIDENCE — do not select a provider yet. The supplied notes identify three candidates but contain no verified offer details, workload, data constraints, budget, or test results. No candidate can be responsibly ranked until those inputs are collected and hard gates are checked.
Buying objective
Evaluate providers for a customer-support triage pilot. The target outcome and baseline are
not supplied. Define the current workflow, target resolution/triage quality, volume, peak concurrency, response-time needs, and human-review process before scoring.
Requirements to confirm
| Requirement | Priority | Evidence / measurement needed |
|---|---|---|
| Correctly classify and route representative support cases | MUST (provisional) | Buyer-owned labeled test set; agreed quality threshold |
| Handle the expected data and sensitivity | MUST | Data flow, retention, training use, deletion, processing location, contractual evidence |
| Integrate with the existing support system | MUST (if required) | Named system, exact product/tier, documented API or connector, implementation test |
| Meet budget and operating-cost ceiling | MUST (threshold missing) | Expected/peak workload and comparable quote or current official pricing |
| Meet latency, availability, and support needs | SHOULD pending thresholds | Buyer thresholds and exact-tier documentation / contract |
The priorities above are a starting hypothesis from the stated pilot, not confirmed buyer policy. Confirm or revise them before excluding any offer.
Candidate comparison
| Candidate | Product / tier | Gate status | Fit | Evidence confidence | Next action |
|---|---|---|---|---|---|
| Candidate A | Unknown | Not assessed | Unknown | None supplied | Request exact product, tier, region, deployment, documentation, and quote |
| Candidate B | Unknown | Not assessed | Unknown | None supplied | Request the same evidence set |
| Candidate C | Unknown | Not assessed | Unknown | None supplied | Request the same evidence set |
No winner or score assigned: product identities, capabilities, restrictions, prices, and security terms were not provided. Do not interpret this table as a current market comparison.
Three-week POC outline
Week 1 — Prepare: confirm MUST gates, data permissions, exact offers, test cases, baseline, success thresholds, owners, and stop conditions. Use approved, minimized data; do not send sensitive customer data to a provider until authorized controls are verified.
Week 2 — Test: run the same representative normal, difficult, edge, multilingual, and safety cases against each eligible offer. Record routing quality, critical errors, latency, reliability, integration effort, human-review load, and usage needed for cost modeling. Keep test conditions and scoring consistent.
Week 3 — Decide: compare results with thresholds set in advance, calculate scenario-based TCO from measured workload and verified prices, document failures and uncertainty, and select only if all MUST gates pass. Otherwise extend the evidence phase or report no current match.
Inputs needed next
- Expected cases per month, peak concurrency, languages, and response-time threshold.
- Support platform and required integrations.
- Data classification, allowed processing regions, retention/deletion rules, and prohibited uses.
- Budget ceiling, deployment preference, timeline, and support requirements.
- Candidate names and exact product/tier offers, official evidence, quotes, and any existing test results.
Reverify before contracting: prices, usage limits, product/tier scope, region availability, data terms, security controls, support commitments, and contract terms.
Connects securely to your tools. The creator never sees your data.
About this skill
Choose AI providers with evidence, not guesswork
AI Vendor Matchmaker turns a business need into a structured, buyer-side evaluation of AI providers and exact product offers. It helps teams define measurable requirements, separate hard gates from preferences, compare technical and commercial fit, plan a realistic proof of concept, and document a defensible selection with a backup and exit path.
What it does
- Clarifies the business outcome, workload, users, data, regions, integrations, budget, and timeline.
- Converts vague goals into testable MUST, SHOULD, COULD, and PROHIBITED requirements.
- Builds an evidence register and distinguishes verified facts from vendor claims, supplied information, calculations, inferences, and unknowns.
- Compares exact products, tiers, models, regions, deployment modes, support levels, and usage commitments on a consistent basis.
- Assesses capability, quality, performance, integration effort, privacy, security, governance, reliability, support, implementation, and portability.
- Normalizes total cost of ownership and flags possible hidden costs, switching costs, concentration, and lock-in.
- Designs buyer-task POCs with acceptance criteria set before testing; prepares vendor questions and negotiation points.
MATCH-AI™ method
Mission → Absolute Requirements → Technical Fit → Commercial Fit → Human & Operational Fit → Assurance → Implementation Decision. Hard gates are applied before any optional fit score. Evidence confidence stays separate from fit, and recommendations make uncertainty and trade-offs visible.
Deliverables
Depending on the request, receive an intake summary, requirements matrix, RFI/RFP/RFQ questions, normalized comparison table, evidence log, TCO scenarios, risk and portability review, shortlist, POC plan, negotiation brief, selection memo, or replacement/exit plan.
Evidence and boundaries
When current research is available, material product facts should be checked against current official documentation and recorded with source, date, exact scope, confidence, and re-verification needs. When research or source files are unavailable, the skill uses supplied candidates and clearly labels facts as unknown; it does not invent providers, features, prices, certifications, integrations, benchmarks, SLAs, regions, policies, contracts, or live access. Security acceptance, legal/privacy interpretation, and financial assumptions remain with qualified stakeholders.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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