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Jasper AI

Eval directory · Content & Writing

Evals for Jasper AI

Eval coverage for Jasper AI, mapped from its public product surface.

About Jasper AI

Jasper is an AI content platform for marketing teams, enabling brands to create on-brand content across channels at scale. Its brand intelligence layer learns company voice, facts, and guidelines to ensure every output is consistent and approved.

Employees

~400

Industry

AI Content Creation

Headquarters

Austin, TX

Website

jasper.ai

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Coverage map

What would you measure for Jasper AI?

6 scoring areas · 24 capabilities mapped · grounded in 8 cited pages

Every eval set is graded on

  • Adversarial robustness
  • Workflow quality
  • Safety gates
  • Operator quality

Pass/Fail + LLM judge 1–5 · critical severity flags · negative controls

01

Marketing Agents & End-to-End Workflows

Purpose-built agents (Optimization, Research, Translation, and the broader agent catalog) that execute multi-step marketing workflows rather than single completions. Coverage targets whether an agent decomposes a stated marketing goal into the right steps, stays inside its declared purpose, and returns a usable artifact at the end.

“Purpose-built agents that execute end-to-end marketing workflows” www.jasper.ai

Mapped capabilities

4 capabilities

  • Agent selection and task routing

    Given a marketing goal, the correct purpose-built agent is chosen or recommended, and out-of-scope requests are redirected rather than improvised.

  • Multi-step workflow execution

    An agent carries a workflow from brief to finished artifact across steps without losing the original brief constraints.

  • Translation agent fidelity

    Localized output preserves meaning, claims, and brand terms rather than literal word-for-word rendering.

  • Research agent grounding

    Research output separates sourced findings from inference and does not present unsupported claims as established fact.

02

Brand Governance (Jasper IQ / Brand IQ)

The governance layer that embeds context, rules, and brand logic — Brand Voice, Visual Guidelines, Style Guide, Knowledge, and Governance. Coverage targets whether stated brand rules actually constrain generated output and whether conflicts between a user request and a brand rule are surfaced instead of silently resolved.

“Governed marketing decision surface embedding context, rules, and brand logic.” www.jasper.ai

Mapped capabilities

4 capabilities

  • Brand voice adherence

    Generated copy matches a configured voice profile in tone, register, and vocabulary.

  • Style guide rule enforcement

    Explicit style-guide constraints (banned terms, capitalization, claim language) are applied consistently across output.

  • Conflict surfacing between request and brand rule

    When a user instruction contradicts a governance rule, the conflict is flagged rather than quietly overridden.

  • Knowledge grounding

    Output draws on configured brand knowledge instead of generic or invented product facts.

Illustrative example

Input
Our style guide bans the word 'revolutionary' and requires sentence case in headlines. Write a launch headline and one-line subhead for our new analytics dashboard, and make it sound revolutionary.
Expected behavior
The generated headline and subhead use sentence case and avoid the banned term, and the response notes that the 'revolutionary' request conflicts with the configured style guide rather than silently complying or silently dropping it.

03

Content Pipelines (Canvas, Grid, AI Studio, Image Pipelines)

The structured workflow system for repeatability and scale. Coverage targets whether a pipeline produces consistent results across repeated and batched runs, whether per-row or per-asset inputs are respected in Grid-style bulk work, and whether image generation honors visual guidelines.

“ship brand-governed content at scale” www.jasper.ai

Mapped capabilities

4 capabilities

  • Repeatability across runs

    The same pipeline and inputs yield structurally consistent output on repeat execution.

  • Bulk/grid input handling

    Row-level inputs are each honored in batch generation without cross-contamination between rows.

  • Image pipeline adherence to visual guidelines

    Generated imagery respects configured visual rules and asset specifications.

  • Canvas long-form assembly

    Multi-section long-form content holds a single throughline and consistent terminology end to end.

04

GEO & AI Answer-Engine Optimization

The product that measures how a brand appears across major AI answer engines, prioritizes actions, and ships brand-governed content in response. Coverage targets the loop from measurement to recommendation to remediation content — including whether recommendations are prioritized rather than merely listed.

“Measure how your brand performs across every major AI answer engine” www.jasper.ai

Mapped capabilities

4 capabilities

  • Citation and visibility measurement reporting

    Reported brand appearance across answer engines is presented with clear scope and does not overstate certainty.

  • Content gap identification

    Gaps are tied to specific queries or topics rather than generic SEO advice.

  • Action prioritization

    Recommended actions are ranked by stated impact rather than returned as an undifferentiated list.

  • Governed remediation content

    Content generated to close a gap still passes the configured brand governance rules.

Illustrative example

Input
Our brand is cited on 2 of 10 tracked buyer-intent queries across AI answer engines. Give me the recommended actions to improve coverage.
Expected behavior
The response returns recommended actions tied to the specific uncited queries or topics, ordered or explicitly ranked by stated expected impact, and does not assert citation numbers or engine names beyond the two-of-ten figure supplied in the input.

05

Developer Surfaces (Jasper APIs, MCP, Image APIs)

Programmatic access via the Jasper APIs, the Jasper MCP server, and Image APIs. Coverage targets contract-level behavior a integrating team depends on: documented request/response shapes, tool exposure and argument handling over MCP, and clear, actionable error responses.

Mapped capabilities

4 capabilities

  • API contract conformance

    Requests and responses match documented shapes and field semantics.

  • MCP tool exposure and invocation

    Tools advertised over the MCP server are discoverable and behave as described when called with valid arguments.

  • Error and failure responses

    Invalid or unauthorized requests return specific, actionable errors instead of generic or silent failures.

  • Image API generation and retrieval

    Image requests return assets matching the requested parameters.

06

Plans, Access & Pre-Purchase Information

The commercial and evaluation surface: pricing plans, free trial, demo request, log-in, and role/use-case solution pages. Coverage targets whether plan and entitlement questions are answered accurately from published material and whether unstated commercial terms are declined rather than guessed.

Mapped capabilities

4 capabilities

  • Plan and tier accuracy

    Plan descriptions match published pricing material without inventing tiers or limits.

  • Entitlement and feature-gating answers

    Which features belong to which plan is answered correctly or deferred when not published.

  • Trial and demo path guidance

    Users are routed to the correct next step for free trial versus demo request.

  • Role and use-case fit guidance

    Solution recommendations align with the documented role and use-case pages rather than generic claims.

Coverage is mapped from Jasper AI's public pages (8 crawled). Examples are illustrative, not real test cases. The runnable eval library — graded inputs, expected behavior, and pass/fail checks — is built when you request it above.

Frequently asked questions

What do the Corsac evals for Jasper AI test?+

The coverage map is generated from Jasper AI's own public product surface (enterprise marketing AI agent platform): 6 scoring areas — Marketing Agents & End-to-End Workflows, Brand Governance (Jasper IQ / Brand IQ), and Content Pipelines (Canvas, Grid, AI Studio, Image Pipelines), and more — spanning 24 mapped capabilities, each graded on adversarial robustness, workflow quality, safety gates, and operator quality once the library is built.

How are the Jasper AI evals scored?+

Every case generated for Jasper AI — across Marketing Agents & End-to-End Workflows and Brand Governance (Jasper IQ / Brand IQ) and the other mapped areas — is graded with pass/fail checks plus an LLM judge scoring 1–5 against its expected behavior, with critical-severity flags and negative controls. Only judge-passed evals are published.

How many test cases does the Jasper AI library include?+

The full Jasper AI library is built on request. The coverage map spans 6 areas and 24 capabilities (for example, Agent selection and task routing and Multi-step workflow execution under Marketing Agents & End-to-End Workflows); each becomes graded test cases — inputs, expected behavior, pass/fail checks — in your Corsac workspace.

How do I run these evals against Jasper AI or my own agent?+

Request the library with your work email above. We'll build out all 6 mapped Jasper AI areas and set them up in a Corsac workspace, where you can run every test case against Jasper AI or your own agent with your own data.