Codeer.AI is a no-code AI agent evaluation and debugging platform. It helps expert-led teams turn approved service standards into eval cases, judge AI responses, debug failures, and improve agent behavior through natural language.

Who is Codeer.AI for?

Codeer.AI is for expert-led teams, small and medium businesses, customer-facing teams, and internal operations teams that need reliable AI agents but do not want to manage evaluation infrastructure or write code.

Can non-engineers create AI agent eval cases in Codeer.AI?

Yes. Codeer.AI lets non-engineers create realistic eval cases, define expected behavior, and review agent responses through natural language workflows.

How does Codeer.AI help debug AI agent issues?

Codeer.AI compares agent responses against approved scenarios and judgments, surfaces failures, and helps teams identify whether issues come from missing knowledge, unclear instructions, wrong scope, or response quality.

What kinds of AI agent workflows can Codeer.AI verify?

Codeer.AI can verify customer-facing workflows such as sales, support, intake, booking, quoting, and consultation, as well as internal expert assistants for SOPs, policy, compliance, technical judgment, and onboarding.

Verified service behavior for expert-led teams

Your standards controlevery agent conversation.

Codeer helps expert-led teams turn approved service judgment into agents that ask the right questions, find the right approved source, and hand off risky cases with context.

Customer asksWrong item. Replacement today?

Expert ruleShip replacement now; collect return in parallel.

Agent actionCollect order ID, confirm address, and hand off exceptions.

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Finds the right approved source
Collects complete intake
Routes risky cases
Improves from reviewed examples

WHAT THE AGENT CAN DO

What a verified agent can handle.

Start with work your team already understands, then let the agent handle it only inside reviewed boundaries.

Turn vague requests into briefs

Ask the right follow-up questions, collect missing details, and prepare a usable summary before your team steps in.

Find the right approved file or SOP

Locate the matching policy, playbook, product detail, SOP, or expert note, then answer from that approved source.

Prepare the next action

Collect the information needed for booking, quoting, intake, troubleshooting, or follow-up, then move work forward when conditions are clear.

Check work against standards

Review answers, submissions, or decisions against the criteria your experts already use.

Guide teammates through SOPs

Help staff follow decision trees, escalation rules, and approved procedures without waiting for a senior expert.

Route risky cases to a person

Recognize when the verified scope ends, keep the conversation context, and hand off before the agent overreaches.

FIRST WORKFLOW

Start with one repeated workflow.

You do not need to automate everything at once. Start where the question comes up often, the approved standard is clear, and wrong behavior would create rework or risk.

Support questionsIntake and bookingQuote preparationPolicy and SOP guidanceReview against a rubric

How the first launch stays manageableVerified scope first

Choose one repeated category

Pick a conversation your team already sees often and can judge clearly.

Define what good behavior means

Turn expert expectations into scenarios, boundaries, and handoff rules.

Publish only the passing scope

Let the agent serve the verified category while everything else stays routed to a person.

CORE DIFFERENCE

AI you use yourself and AI that serves customers are different problems.

General AI tools work well when an expert is present to judge the answer. Codeer is for customer-facing and team-facing workflows where the agent must follow approved standards without constant supervision.

Using AI yourself

AI serving your customers

Who judges quality

•You do, because you can redirect the AI every conversation

•The customer may not know what went wrong

When the answer is wrong

•Retry, add context, or ask a sharper question

•Brand damage, complaints, or operational risk

Control requirement

•Low, exploration is often the point

•High, repeated behavior must be predictable

Beyond capability

•You know when to stop

•The agent needs handoff, scope, and safety gates

Go-live process

•No launch process needed

•Version control, behavior verification, and scope control

With customers, approved behavior matters more than raw capability.

SCENARIO TESTING

Review agent answers before they reach real users.

Codeer turns real situations and approved standards into a case library. Run every agent version against the same cases, then fix the answers that do not meet your standard.

1Start with a real situationEach case is a concrete request the agent must handle correctly.2Run the current answerCodeer records what this version of the agent actually says.3Check the approved standardThe answer is judged against explicit requirements, and the gap is explained.4Decide what shipsThe agent leaves draft only after every eval case passes.

CaseUser situationEvaluatorResult

Policy exception request#14A user asks the agent to approve an exception outside the published policy.Boundary rule0.61 | Needs review

Missing source#15A user asks what the uploaded policy says about cancellation after approval.Source citation0.78 | Revise

Review criteria#16A user asks why their request did not meet the required standard.Criteria match0.94 | Pass

AGENT LIFECYCLE

Build one useful version. Expand only after the next loop passes.

Start with a narrow workflow, test the boundaries, publish the stable scope, then use real feedback to decide what belongs in the next version.

Build v1

Draft one workflow the team already knows well.

Test

Run core, boundary, and fallback cases.

Publish

Release only the stable scope.

Learn

Review feedback, handoffs, and missed replies.

Add cases

Turn useful feedback into draft tests.

Rerun

Check new cases and the old suite together.

Publish v1.1

Expand only after the wider scope passes.

The published agent only moves when the cases pass.Feedback becomes reusable test coverage, so each version grows from behavior your team has reviewed.

PRICING

Simple, transparent pricing

One organization price. No per-seat or per-student fees.

SStarter

From$40/mo

500 credits5 team members (unlimited end users)

Popular

PPro

From$150/mo

3,000 credits20 team members (unlimited end users)

BBusiness

From$500/mo

12,000 creditsUnlimited team members & end users

Cancel anytimeFlexible credit top-upsUsage alerts + spending caps

See full plan comparison

Working with teams that need AI to follow real expert judgment.

Professor Ji-Ren Lee

Nii School

ChuanVet

Chengzhi Education Foundation

Build verified service behavior. For customers or your team.

Start with one high-value workflow, define the standards, verify the behavior, then iterate from real conversations.