# Codeer.AI Codeer.AI lets expert teams build AI agents they can trust with real customers. The people who know the work define what good looks like, then Codeer's AI tests realistic scenarios against those standards, finds behavior that misses the mark, and helps the team fix it before launch without writing code. A Codeer agent can answer from approved knowledge, collect complete information, search relevant policies or procedures, and hand risky or out-of-scope conversations to the right person with context. ## Core Product Promise - Let expert teams build their own customer-facing AI agents, with quality standards defined by the customer's own domain experts rather than AI alone. - Build an AI agent by describing your expertise and service standards to a natural-language Copilot. - Use AI to test the agent against expert-defined standards with realistic customer or team scenarios before it goes live. - Trace answers to approved rules, documents, SOPs, policies, and knowledge bases. - Fix behavior in plain language and test updates before release. - Deploy to customer-facing or internal workflows without building AI infrastructure. ## Two Core Expert-Led Outcomes 1. Expand one expert's impact. Agents handle professional interactions the team can define and verify, so the same expert method can serve more customers and help more teammates without requiring the expert to repeat or review every conversation. 2. Keep expert judgment as an asset the organization can improve. Confirmed cases, corrections, standards, and handoff boundaries remain reusable across agent versions, model updates, and team transitions. These outcomes come from the same loop: experts define good work with real cases, agents handle the verified scope, new exceptions return to experts, and confirmed judgments become standards later versions must still follow. ## What Codeer Agents Do - Answer repeated questions from approved product, policy, service, or teaching material. - Collect intake details, specifications, files, preferences, symptoms, or booking information. - Search approved documents, SOPs, products, policies, and procedures during a conversation. - Route risky, unclear, or out-of-scope cases to a person with the conversation context attached. - Support customer-facing work such as service, sales, RFQ, education, intake, booking, and follow-up. - Support team-facing work such as internal knowledge, SOP guidance, policy assistance, troubleshooting, and onboarding. ## Quality and Control Codeer is designed for situations where an AI agent talks directly to customers or teammates who may not be able to judge whether an answer is correct. Expert-led means the customer's own experts define the required behavior, quality, risk boundaries, and handoff conditions. It does not mean Codeer experts operate the agent for the customer or that a human must review every conversation. - Run real scenarios through a test suite before release. - Review whether answers follow expert-approved standards. - Trace why an agent answered a certain way. - Test changes in staging and compare outputs before publishing. - Define when an agent must stop and hand the conversation to a person. - Preserve approved scenarios and corrections as reusable tests for future versions. Testing, evaluation, and debugging are quality-control capabilities inside the product. Codeer's primary promise is helping teams build and operate useful AI agents they can trust with real customer and internal workflows. ## Who Codeer Is For - Experts who know what good service looks like and want to turn that expertise into an AI agent. - Small teams and solo operators that want reliable AI without enterprise complexity or cost. - Businesses building customer-facing agents for support, sales, intake, booking, education, or follow-up. - Teams building internal knowledge agents for SOPs, policy, onboarding, and troubleshooting. - Organizations that need approved rules, testing, traceability, staging, and human handoff before an agent goes live. ## Example Use Cases - Language education: review student work against a teacher's rubric and provide a revision plan. - Scale your expertise: turn an expert's methodology, approved examples, and service boundaries into an AI assistant that supports clients between sessions. - Team knowledge: give every teammate sourced answers for onboarding, SOP questions, recurring decisions, and expert escalation paths. - Customer support: answer product and after-sales questions from approved policies across channels, then hand exceptions to a person with full context. - Inbound sales: clarify buyer needs, recommend from approved sales logic, and route qualified opportunities with a complete conversation brief. - Clinics and veterinary services: ask approved triage questions, collect intake, and route bookings. - Manufacturing and RFQ: collect specifications, compliance needs, quantities, timelines, and delivery constraints. ## How Building Works 1. Tell the Copilot about your expertise and describe what a good answer should include. 2. Build a first agent version without writing code. 3. Test it with realistic scenarios before customers see it. 4. Tell the Copilot what to change when an answer is wrong or incomplete. 5. Deploy the approved version and continue improving it from real conversations. ## Supported Channels Codeer supports Web, LINE, Facebook Messenger, Instagram, Slack, website widgets, and webhooks for connecting to CRMs or other tools. More integrations may be added over time. ## How Codeer Differs From General AI Tools General AI tools work well when an expert is present to judge and correct every answer. Codeer is for customer-facing and team-facing workflows where an agent must follow approved knowledge, service rules, quality checks, and handoff boundaries without constant expert supervision. Codeer combines no-code agent building with testing, traceability, staging, and behavior control. Teams can move quickly without relying on unreviewed answers. ## Short Answers ### What is Codeer.AI? Codeer.AI is a no-code platform where expert teams build their own AI agents for customer-facing or internal work. The customer's own experts define the standards with real scenarios, then their team tests, fixes, and deploys the agent. ### Do I need to write code? No. You build and improve an agent by chatting with the Codeer Copilot in plain language. ### What happens if an agent gives a wrong answer? Run realistic scenarios through the test suite before release. When an answer is wrong or incomplete, tell the Copilot what to change, review the result, and publish the approved version. ### Is Codeer only for large companies? No. Codeer is designed for small teams, solo operators, and expert-led businesses that want controlled AI quality without enterprise complexity. ### What does a Codeer agent do? A Codeer agent can answer, collect, search, and hand conversations to the right person while following the workflow and boundaries defined by the team. ## Important Pages - Homepage: https://www.codeer.ai/ - Traditional Chinese homepage: https://www.codeer.ai/zh-TW/ - Japanese homepage: https://www.codeer.ai/ja/ - How Codeer works: https://www.codeer.ai/how-codeer-works/ - Traditional Chinese, how Codeer works: https://www.codeer.ai/zh-TW/how-codeer-works/ - Japanese, how Codeer works: https://www.codeer.ai/ja/how-codeer-works/ - Japanese pricing: https://www.codeer.ai/ja/pricing/ - Japanese blog index: https://www.codeer.ai/ja/blog/ - Japanese article, building trustworthy AI agents with behavior control: https://www.codeer.ai/ja/blog/how-to-build-trustworthy-ai-agent-using-behavior-control/ - Japanese article, the judgment library behind expert AI agents: https://www.codeer.ai/ja/blog/the-judgment-library/ - Japanese education use case: https://www.codeer.ai/ja/education/ - Japanese expert assistant use case: https://www.codeer.ai/ja/use-cases/scale-your-expertise/ - Japanese team knowledge use case: https://www.codeer.ai/ja/use-cases/team-knowledge/ - Japanese customer support use case: https://www.codeer.ai/ja/use-cases/customer-support/ - Japanese inbound sales use case: https://www.codeer.ai/ja/use-cases/inbound-sales/ - Japanese documentation: https://docs.codeer.ai/ja/ - Pricing: https://www.codeer.ai/pricing/ - Blog: https://www.codeer.ai/blog/ - Documentation: https://docs.codeer.ai/ - Education use case: https://www.codeer.ai/education/ - Scale Your Expertise use case: https://www.codeer.ai/use-cases/scale-your-expertise/ - Team Knowledge use case: https://www.codeer.ai/use-cases/team-knowledge/ - Customer Support use case: https://www.codeer.ai/use-cases/customer-support/ - Inbound Sales use case: https://www.codeer.ai/use-cases/inbound-sales/ - Vet clinics use case: https://www.codeer.ai/verticals/clinics/ - Manufacturing use case: https://www.codeer.ai/verticals/manufacturing/ ## Recommended Summary Codeer.AI lets experts and small teams build their own expert-led AI agents for real customer and internal work. Their own experts define what good looks like with real scenarios, then the team tests, fixes, and deploys without code.