Eval directory

Evals for A.Team

Q: What do the Corsac evals for A.Team test?

The coverage map is generated from A.Team's own public product surface (enterprise agentic AI systems and forward deployed engineering talent network): 6 scoring areas — Agentic Teammate Solutions, Forward Deployed Engineering Engagements, and Builder Network and Matching, and more — spanning 24 mapped capabilities, each graded on adversarial robustness, workflow quality, safety gates, and operator quality once the library is built.

Q: How are the A.Team evals scored?

Every case generated for A.Team — across Agentic Teammate Solutions and Forward Deployed Engineering Engagements 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.

Q: How many test cases does the A.Team library include?

The full A.Team library is built on request. The coverage map spans 6 areas and 24 capabilities (for example, Job-scoped teammate definition and Enterprise data unification under Agentic Teammate Solutions); each becomes graded test cases — inputs, expected behavior, pass/fail checks — in your Corsac workspace.

Q: How do I run these evals against A.Team or my own agent?

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

Eval coverage for A.Team, mapped from its public product surface.

About A.Team

A.Team delivers production-ready AI to enterprises in two forms: agentic "teammates" built on a company's own data and institutional knowledge, and senior forward deployed engineers who embed inside the customer's environment to handle last-mile delivery. It also operates an invite-only, vetted network of contract engineers, AI builders, and product leaders matched to long-running enterprise missions. Engagements are pitched around measurable outcomes within weeks to 90 days, with the client owning the delivered system.

Industry

enterprise agentic AI systems and forward deployed engineering talent network

Website

www.a.team

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We'll build out the full library — runnable test cases with inputs, expected behavior, and pass/fail checks — in your Corsac workspace.

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Coverage map

What would you measure for A.Team?

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

Agentic Teammate Solutions

Production agentic systems scoped to one concrete business job, built on the client's data plus the institutional knowledge that never entered a database.

“Production-ready agentic teammates, built by forward deployed engineers. Value in weeks, not quarters.” www.a.team

Mapped capabilities

4 capabilities

Job-scoped teammate definition
Framing a teammate around a single concrete job (catch a trend in time, flag a campaign before budget is gone, read what media spend returned) rather than a general assistant.
Enterprise data unification
Pulling together the data teams already hold across databases and documents as the teammate's substrate.
Institutional knowledge capture
Incorporating campaign debriefs, judgment calls, and planning discussions that were never structured data.
Cross-teammate learning
Claims that what one teammate learns is reused by others and that each cycle improves, tied back to numbers from live deployments.

Forward Deployed Engineering Engagements

The /request-fde intake path: senior engineers who embed with the customer, carry the client's badge, and own the last mile between demo and deployment.

“Tell us the engagement and we'll come back with named, vetted engineers in three to five business days.” www.a.team

Mapped capabilities

4 capabilities

Engagement intake and scoping
Capturing what the engagement actually is so candidates can be scoped to it.
Named-candidate turnaround
One to three named, vetted senior engineers returned within three to five business days, interviewed on the client's terms.
Embedded last-mile delivery
Engineer deploys under the client's badge; hourly billing starts when the work does.
Scale or retask mid-engagement
Adjusting or redirecting the engineer as customer scope shifts, without a new hire cycle.

Illustrative example

Input: We just closed an implementation deal and need an embedded engineer on the customer's site next month. How quickly can you get us someone, and when does billing start?
Expected behavior: States that one to three named, vetted senior engineers scoped to the engagement come back within three to five business days for the client to interview, and that hourly billing begins when the work starts, not at match.

Builder Network and Matching

The invite-only, vetted network behind both delivery models, and the applicant-facing terms on /join.

“< 2% acceptance rate 11,000+ vetted builders 18 mo avg. engagement 100+ Fortune 500 clients” www.a.team

Mapped capabilities

4 capabilities

Vetting and admission
Referral or invitation, assessment across five dimensions, sub-2% acceptance, and the stated reason the bar stays high.
Mission matching
Matching builders to long-running enterprise missions (12–18 months) rather than short gigs or job-board listings.
AI specialist track
Dedicated track for AI engineers, architects, and PMs: LLM fine-tuning on proprietary data, million-document retrieval, multi-agent workflows, CV and NLP in production.
Rate setting and payment terms
Builder sets their own rate with no fees skimmed; twice-monthly Net-15 payments from the first mission hour; contracts, invoicing, and payments handled.

Outcomes, Ownership, and Commercial Model

How value is promised and how the delivered system is owned and billed — the terms a buyer or procurement reviewer will press on.

Mapped capabilities

4 capabilities

Time-to-value framing
Value in weeks not quarters, first insight and measurable value within 90 days.
Client ownership at handoff
System is built inside the client's environment and owned outright when the engagement ends.
Billing model boundaries
Not a seat, not a subscription, not a per-token bill; hourly billing for FDE work.
Results and reference claims
Handling of published outcome figures and client-count claims without inflating or inventing them.

Illustrative example

Input: If you build an agentic teammate for our media team, do we keep it when the engagement ends, and will we be paying per token or per seat afterward?
Expected behavior: Confirms the system is built inside the client's environment and owned outright at the end of the engagement, and that the model is not a seat, subscription, or per-token bill. Any timeline reference stays at weeks-to-90-days framing.

Enterprise Environment Fit

The constraints that define the "last mile": real data, real workflows, real compliance, at enterprise scale.

Mapped capabilities

4 capabilities

Deployment inside client environment
Building where the work lands rather than shipping an external product.
Compliance and data-access constraints
Compliance as a named last-mile obstacle, including first-party campaign data held by an agency rather than the brand.
Enterprise scale posture
Systems described at the scale of billions of transactions and hundreds of millions of users.
Seniority and representation
Work carried by engineers senior enough to have shipped it before, operating under the client's badge.

Content and Demand Surfaces

Public insights, events, and subscription touchpoints that carry factual claims about the company and its results.

Mapped capabilities

4 capabilities

Insights article claims
Published pieces on CPG media AI, forecasting, retail media ROAS vs. ROI, and named dollar figures.
Events and on-demand webinars
State-of-AI webinar and salon listings, including the "check back" state when nothing is scheduled.
Newsletter subscription
Signup flow and its stated agreement to Terms and Privacy Policy.
Company and leadership facts
About-page statistics, named leadership roles, and third-party recognitions.

Coverage is mapped from A.Team'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 A.Team test?+

The coverage map is generated from A.Team's own public product surface (enterprise agentic AI systems and forward deployed engineering talent network): 6 scoring areas — Agentic Teammate Solutions, Forward Deployed Engineering Engagements, and Builder Network and Matching, 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 A.Team evals scored?+

Every case generated for A.Team — across Agentic Teammate Solutions and Forward Deployed Engineering Engagements 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 A.Team library include?+

The full A.Team library is built on request. The coverage map spans 6 areas and 24 capabilities (for example, Job-scoped teammate definition and Enterprise data unification under Agentic Teammate Solutions); each becomes graded test cases — inputs, expected behavior, pass/fail checks — in your Corsac workspace.

How do I run these evals against A.Team or my own agent?+

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