# AthenaHQ credit and editorial evaluation Decide whether to keep, resize or replace the observation panel. Price the required workload and assign the work from recommendation to publication before comparing candidates. Worksheet version 1.0 · 17 September 2026. Complete one record per candidate. Blank fields request your evidence; this pack does not report vendor account tests or executed pilots. Complete comparison: https://rankecho.io/compare/athenahq-alternatives ## 1 Define the required panel Use one record per candidate, including AthenaHQ. Set the requirements before testing. **Decision and owner** — Record the candidate, evaluator, client or brand, decision date and reason for considering a change. [Enter your response] **Prompts and locations** — Link the exact prompt list and one owned page. Record location, language, persona settings and the answer surfaces you need. [Enter your response] **Must haves and budget** — Set required cadence, history, exports, review controls and a monthly spending ceiling. State what would make you keep the incumbent. [Enter your response] ## 2 Calculate credits and headroom The public calculator cases were reproduced on 17 September 2026. All use 20 prompts, one location, seven days per week, zero personas and 4.33 weeks. The base models are ChatGPT, Google AI Overviews and Perplexity at one credit each; Claude costs five. Fan out on multiplies credits by four. These are estimates, not invoices. **Model weights and repetitions** — List selected models and credits per response, prompts per location, locations, days per week and fan out. Test persona settings separately; the examples use zero personas. [Enter your response] **Monthly estimate and reserve** — Calculate prompts × locations × sum of model weights × fan out × days per week × 4.33. Record rounding, included credits, reserve and extra credits needed. [Enter your response] **Quote and billing terms** — Attach the dated calculator capture and written quote. Record subscription, extra credits, API cost, commitment, cancellation, tax and implementation labor. [Enter your response] | Example panel | Credits per run | Credits per month | | --- | --- | --- | | 3 models, fan out off | 60 | 1,819 | | Add Claude, fan out off | 160 | 4,850 | | Same 4 models, fan out on | 640 | 19,398 | ## 3 Test the editorial handoff Run one prompt cluster and owned page through the proposed workflow. Keep test drafts unpublished until review is complete. **Recommendation and artifact** — Save the original gap, cited sources and recommendation. Identify whether the deliverable is guidance, a brief, a draft or an approved change. [Enter your response] **Review and claim correction** — Assign writer and reviewer. In an unpublished test, check whether a deliberately incorrect claim is caught, corrected and recorded before approval. [Enter your response] **Publication and rollback** — Name the publisher, required permissions, approval record, page diff, scheduled shipment and rollback owner. Verify the actual integration on the quoted plan. [Enter your response] **Export and observation** — Save an actual permitted export with prompt text, model, settings, timestamps, answer and citations. Define the later observation window and how unavailable results are labelled. [Enter your response] ## 4 Record the decision Choose the least expensive configuration that passes the requirements. A smaller panel or no switch can be a valid result. **Pass or fail with evidence** — For each must have, record pass, fail or untested, the evidence link and unresolved cost or ownership questions. [Enter your response] **Stay resize or replace** — Record the selected option, tradeoffs, approved budget and sign off. Separate a changed answer from evidence that publication caused the change. [Enter your response] **Handoff and exit** — Assign exports, open drafts, client reports, billing dates and access removal. State the acceptance date and condition that would reverse the decision. [Enter your response] ## Complete comparison guide Stay with AthenaHQ when the observation panel, integrations, actions, and governance fit the purchased scope. Consider Peec AI for daily monitoring and prioritized guidance with an editorial team, AirOps for repeated content-production workflows, or RankEcho for bounded fixes and post-shipment observations. Model availability does not establish an affordable cadence: price the required panel before comparing plans. Original guide update: 2026-09-12. Companion and scoped source recheck: 17 September 2026. The evidence records below retain their individual dates. Confirm current plan, billing commitment and workload in a written quote. AthenaHQ pricing and calculator rechecked 17 September 2026: Starter remains $295/month with 3,600 credits; API and extra credits are paid add-ons. The three original zero-persona calculator cases reproduced 1,819, 4,850 and 19,398 monthly credits. Model weights and fan-out matter; obtain a quote for the required workload. Earlier source records retain their original dates. [AthenaHQ plans](https://athenahq.ai/plans) · [AthenaHQ calculator](https://athenahq.ai/credit-calculator) ## Which option fits the panel and content job? Separate observation from production. First price the models, regions, prompts, cadence, and repeats you need; then decide who turns a gap into a brief, draft, approval, publication, and later observation. Published by RankEcho from official documentation and three public AthenaHQ calculator scenarios, without paid-account tests. Prices and claims were checked on September 12, 2026; they exclude tax, implementation, negotiated terms, and unlisted add-ons. | Option | Strong fit | Published cost basis | Poor fit or must-have gate | | --- | --- | --- | --- | | AthenaHQ | Integrated visibility, actions, exports, and analytics or CMS connections when the weighted panel fits the purchased credits. | Starter is $295 monthly with 3,600 credits; Enterprise is custom. A 17% annual discount is advertised. API access and extra credits are paid add-ons priced by contact. | Starter lists 11 models, one region and language, unlimited seats with RBAC, and base optimization. The plan page and calculator describe credit use differently; price the chosen models and fan-out in the calculator and confirm the order form. | | Peec AI | Daily monitoring and prioritized Actions for a team that already owns editorial production. | Monthly brand plans: Starter $95, Pro $245, Advanced $495; Enterprise is custom annual. Extra models cost extra. | Starter, Pro, and Advanced include 50, 150, and 350 prompts across one, two, and five projects, with three selected models. Prompts are shared across projects, and usage still counts for region or language variants. Peec says the customer creates the content. | | AirOps | Repeated editorial production with configurable workflows, context sources, human handoffs, and CMS publishing. | No recurring plan amount is public; obtain a quote for Solo, Pro, or Enterprise, including task period, eligible steps, overages, term, and required review or publishing scope. | Solo lists ChatGPT-only insights, 35,000 content tasks, one brand kit, three knowledge bases, and one user. Pro lists seven or more answer engines, 100,000 tasks, one brand kit, five knowledge bases, and unlimited seats. A task is not necessarily an article. | | RankEcho | Reviewable fix artifacts, manual shipment, and same-prompt observations when the team owns publishing and needs a bounded change. | Monthly: Solo $49, Growth $149, Agency $399; annual billing gives two months free. Full-page writing requires a paid base plan plus a content add-on from $99 monthly for 10 pieces. | Solo, Growth, and Agency include 100, 500, and 2500 prompt slots across 1, 3, and 25 domains. No automatic CMS execution, native GA4 connector, enterprise AirOps-equivalent workflow, or Copilot check is included. | - [AthenaHQ plans](https://athenahq.ai/plans) - [Peec AI pricing](https://peec.ai/pricing) - [AirOps pricing](https://www.airops.com/pricing) - [RankEcho pricing](https://rankecho.io/pricing) - [RankEcho content add-on](https://rankecho.io/pricing/content) ## When should you stay with or resize AthenaHQ? Stay when the required panel, integrations, exports, action workflow, and governance controls fit the purchased plan and a representative month leaves an agreed credit reserve. The credit model is a workload basis to verify, not an inherent defect. Resize when the important buyer questions remain valuable but every model, region, or daily run is not required. Preserve decision-critical prompts and adverse results; narrow cadence or model scope by business need rather than deleting unfavorable observations to improve a visibility score. Replace AthenaHQ when the tested panel still fails budget or scope, or when the required editorial handoff cannot be made reviewable on the quoted plan. API access, extra credits, broader regions, and advanced governance belong in the written configuration before a switch decision. - [Review AthenaHQ plan gates](https://athenahq.ai/plans) - [Keep the buyer-prompt panel decision-led](https://rankecho.io/templates/prompt-portfolio-b2b-saas) ## How does AthenaHQ's weighted calculator change the choice? At zero personas, the calculator multiplies prompts, locations, model-weight sum, days per week, 4.33 weeks, and fan-out. These cases use 20 prompts, one location, and seven days weekly; monthly totals are rounded. Claude weighs five; the other three tested models weigh one. Fan-out adds three variations, multiplying use fourfold. The middle case prompted an add-on recommendation without a verified unit price. These are projections, not usage or invoices; personas were untested. | Selected models | Weight sum | Fan-out | Credits / run | Displayed / month | Decision signal | | --- | --- | --- | --- | --- | --- | | ChatGPT + Google AI Overview + Perplexity | 3 | 1× | 60 | 1,819 | Within Starter before reserve. | | Add Claude | 8 | 1× | 160 | 4,850 | Above Starter; narrow or quote. | | Same four models | 8 | 4× | 640 | 19,398 | Confirm fan-out and quote. | - [Reproduce the public calculator scenarios](https://athenahq.ai/credit-calculator) ## How do the alternatives change the editorial handoff? Peec AI fits when monitoring and prioritization should end in a clear editorial queue: its Actions documentation leaves content creation with the customer. AirOps fits when a repeated production workflow should combine models, data, research, human approval, and CMS publishing; its Human Review step can pause for edits, but the required commercial tier must be quoted. RankEcho fits a smaller manual-shipment process with reviewable artifacts and a separate full-page add-on. For RankEcho eligibility, Free audits check Perplexity and Gemini once per prompt. Paid and trialing accounts add ChatGPT, Claude, and Google AI Overviews when configured for the account, for up to 5 engines. Google AI Overviews is reported only when an overview is shown and retrievable; otherwise that cell is marked skipped/unavailable rather than counted as a citation miss. RankEcho does not currently run Microsoft Copilot checks. Its Gemini check uses a Developer API model with Google Search, not Gemini Apps. Solo re-tests weekly; Growth and Agency re-test daily. A content piece is 1,500 generated words rounded up with a one-piece minimum. The sample is fictional, and Proof Loop comparisons are correlational rather than causal. - Recommendation: name who accepts the observed gap, source evidence, priority, and intended page rather than allowing a score to start production automatically. - Brief and draft: record who supplies approved facts and dated sources, what the tool creates, what a human must add, and which usage unit is consumed. - Review: test one clearly marked bad claim in an unpublished evaluation. Require the workflow to pause, preserve the edit, and prevent publication until the named reviewer accepts it. - Publish: name the CMS owner, permissions, proposed diff, rollback path, and ship date. Do not equate a recommendation, generated draft, or accepted review with a live page. - Observe: repeat the fixed panel after shipment and retain improvement, decline, no change, and unavailable results without claiming the content caused the movement. - [Peec AI Actions and content boundary](https://peec.ai/product-actions) - [AirOps Human Review documentation](https://docs.airops.com/actions/workflow-concepts/workflow-steps/flow/human-review) - [AirOps workflow concepts](https://docs.airops.com/getting-started/core-concepts) - [Inspect a bounded RankEcho fix](https://rankecho.io/sample-fix) ## What should the evaluation worksheet record? Use one actual buyer-prompt cluster and one owned page. Record the approved facts, dated sources, required regions and languages, required and optional models, minimum useful cadence, fan-out or repeat policy, monthly budget, reserve, report fields, reviewer, shipper, and decision date. - Run the same initial panel and record available results, unavailable cells, raw answers, source URLs, unit consumption, estimated full-month usage, and every plan or add-on gate. - Give content-capable options the same gap and source pack. Save the recommendation, brief, draft, human edit, approval, publishing boundary, final artifact, and staff time at each handoff. - Request the same report and raw export. Check prompt text, model or surface labels, configuration, timestamps, answers, citations, availability, and retention with the actual file. - Select the least expensive configuration that passes all must-haves, including editorial ownership. Keep an incumbent or narrower panel when no replacement passes. - [Build a fixed SaaS prompt panel](https://rankecho.io/templates/prompt-portfolio-b2b-saas) - [Classify later observations carefully](https://rankecho.io/resources/prove/change-vs-noise) ## What must you preserve before switching? Before cancelling, export every permitted prompt, model or surface label, location, persona setting, cadence, fan-out or repeat rule, raw answer, source URL, unavailable state, timestamp, metric definition, content artifact, approval, report, role, billing date, and contract term. Run both configurations for one reporting cycle when practical. If labels, sampling, model identity, availability handling, or denominators differ, close the old series and start a dated baseline rather than joining incompatible percentages. Missing or unavailable results are not negative visibility observations. Assign ownership of exports, drafts, CMS changes, integrations, credentials, open reviews, and client reports. Revoke access through normal account controls after the accepted handoff and retain the offboarding record. ## What should you verify again before signing? Recheck prices, credit weights, fan-out and persona behavior, prompt and model allowances, regions, cadence, tasks, content units, exports, retention, API and integration scope, review and publishing permissions, and contract terms. For RankEcho, also recheck configured engines, Google AI Overview availability, Copilot, content-add-on, manual-shipment, sample, and Proof Loop boundaries. Save the dated plan page, calculator inputs and outputs, quote, order form, export sample, evaluation record, and unresolved questions. Resolve a decision-critical conflict in the tested account and signed terms before cancelling AthenaHQ. ## Should we remove an expensive model or low-performing prompt? Only when it no longer represents a decision-critical buyer question or required observation surface. Narrow the panel or cadence using declared business criteria; do not remove adverse results merely to improve a reported score. ## Which option creates finished content? Peec AI documents guidance while leaving content creation to the customer. AirOps documents production workflows with human approval and CMS publishing, subject to the quoted tier. AthenaHQ lists base or advanced content-optimization agents by plan. RankEcho full-page writing is a separate paid-plan add-on. Test one real handoff before treating any scope as equivalent. ## Can an AthenaHQ history continue unchanged in another tool? Do not assume so. Export the full configuration and raw records, then compare labels, sampling, availability rules, model identity, and denominators. Begin a dated baseline when the units are not portable. ## Preserved dated evidence - [AthenaHQ plans](https://athenahq.ai/plans) — checked 2026-09-12. AthenaHQ's plans were reviewed for price, allowances, integrations, regions, governance, and add-ons. Current public Starter and Enterprise plan comparison No account, response, integration, credit purchase, checkout, website allowance, or agency quote was tested. Confidence: High - [AthenaHQ credit calculator](https://athenahq.ai/credit-calculator) — checked 2026-09-12. AthenaHQ's public calculator applies model-specific credit weights and a fourfold fan-out multiplier to projected usage. Public calculator; three fixed zero-persona scenarios Public UI only; arithmetic was checked. No personas, account usage, entitlement, add-on purchase, or invoice was tested. Confidence: High - [Peec AI pricing](https://peec.ai/pricing) — checked 2026-09-12. Peec AI's live US-dollar brand pricing was reviewed for monthly tier prices, prompts, selected models, projects, tracking cadence, users, and Enterprise scope. Live US-dollar monthly brand view No account, model selection, region, language, prompt meter, project, export, agency bundle, billing flow, or annual discount was tested in this review. Confidence: High - [Peec AI Actions](https://peec.ai/product-actions) — checked 2026-09-12. Peec AI describes Actions as citation and content-type grouping with prioritized owned and off-page guidance; it says the customer still creates the content. Current public Actions product page This is a documentation review. Recommendation quality, prioritization, editorial work, publishing, and later visibility were not tested. Confidence: High - [AirOps pricing](https://www.airops.com/pricing) — checked 2026-09-12. AirOps' current cards list Solo, Pro, and Enterprise with different visibility, content-task, seat, region, and context allowances, but no recurring public plan amount. Current Solo, Pro, and Enterprise cards The cards and FAQ were reviewed. No quote, task period, eligible workflow step, overage, trial, checkout, or account was tested; the FAQ also retains older Scale wording. Confidence: High - [AirOps Human Review](https://docs.airops.com/actions/workflow-concepts/workflow-steps/flow/human-review) — checked 2026-09-12. AirOps documents a Human Review step that pauses a workflow for synchronous or asynchronous review, supports edits to one or multiple values, and continues only after acceptance rather than cancellation. Current public workflow-step documentation No workflow or review was run, and this review does not establish that Human Review is included in a particular commercial tier. Confidence: High - [AirOps core concepts](https://docs.airops.com/getting-started/core-concepts) — checked 2026-09-12. AirOps describes workflows that combine models, data, research, human approval, and CMS publishing; Grid can run a workflow across rows, while brand kits and knowledge bases supply context. Current public getting-started documentation The documented concepts were reviewed. No workflow, Grid, context source, approval, CMS connection, publication, or throughput was tested. Confidence: High - [RankEcho pricing](https://rankecho.io/pricing) — checked 2026-09-12. RankEcho's public Solo, Growth, and Agency pricing was reviewed for billing, prompt, domain, seat, and re-test limits and paid Fix and Proof access. Current public pricing and repository plan constants The public page was checked against billing limits in source. No account, engine run, fix, report, integration, or post-change result was tested. Confidence: High - [RankEcho content pricing](https://rankecho.io/pricing/content) — checked 2026-09-12. RankEcho full-page writing and refreshing is a separate add-on that requires a paid visibility plan; its tiers differ in price and piece allowance. Current public content pricing and repository content-plan constants The add-on dependency, prices, allowances, and piece definition were checked against source. No content was generated, reviewed, exported, or published. Confidence: High - [RankEcho sample fix](https://rankecho.io/sample-fix) — checked 2026-09-12. RankEcho's public sample fix is a deterministic fictional example with editable answer-block, schema, brief, source-plan, and review artifacts, not a customer result or promised outcome. Current public deterministic sample The sample was inspected as a documented output preview. It does not establish fit for another page or show that publishing changes an answer or citation. Confidence: High - [RankEcho Proof Loop](https://rankecho.io/product/proof-loop) — checked 2026-09-12. RankEcho's Proof Loop records a baseline, shipment, and later observations for the same configured prompts and engines, framed as correlation with controls rather than causal proof. Current public product and measurement description The documented method was reviewed. No customer series, causal effect, referral, or commercial outcome was tested. Confidence: High ## Related reading ## Product next step Inspect a reviewed change at https://rankecho.io/sample-fix and the Fix Engine at https://rankecho.io/product/fix-engine. Full-page writing is separate and requires a paid base plan plus a content add-on: https://rankecho.io/pricing/content.