Give your agent the precise context for every turn.

Journey issues, playbooks, variables, actions, and knowledge base. Five no-code components that work together to give Emily exactly what she needs so every customer interaction runs the way your best agent would run.

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The co-working model

Guide you through every step of the build.

The co-working model

Guide you through every step of the build.

Product training

We run training sessions with your AgentOps team, walking through how to onboard Emily to your product, policies, and edge cases the right way.

Product manual

A living reference your AgentOps team can rely on from day one, so they get hands-on quickly and build confidently without starting from scratch.

Advisory

We work through your specific use cases with you, fine-tuning best practices and the small details that shape the best customer interactions.

The co-working model

Guide you through every step of the build.

Product training

We run training sessions with your AgentOps team, walking through how to onboard Emily to your product, policies, and edge cases the right way.

Product manual

A living reference your AgentOps team can rely on from day one, so they get hands-on quickly and build confidently without starting from scratch.

Advisory

We work through your specific use cases with you, fine-tuning best practices and the small details that shape the best customer interactions.

Journey & issue

Universe of issues Emily handles.

Most teams build agents bottom-up: a growing list of intents that overlap, conflict, and confuse the model. We take a different approach. Emily’s journey issues are mapped MECE across your user journey, so every conversation routes to the right issue, faster and with less ambiguity.

Playbooks

Agent rules & guardrails.

A domain-specific language that lets Emily enforce critical SOP steps deterministically, while still holding a natural, human-like conversation. You get the reliability of a workflow engine and the flexibility of an LLM, without choosing between them.

Variables

Dynamic turn-level data.

Variables are Emily’s working memory: the business signals she tracks and reasons over in every conversation. Translate raw backend data into meaningful variables, design and test them offline with AI, then execute as code at runtime.

Actions

Tool calls & execution.

The best human agents don’t just answer questions. They clarify intent, remind customers of next steps, collect missing details, verify identity, and exercise judgment. Emily does the same, and executes account-related operations with the precision of a system call.

Knowledge base

Source of truth.

Not a generic RAG layer. Individual knowledge bases are citable directly from Playbooks, and Emily engages with each type differently — answering FAQs concisely, walking through product manuals step by step, and guiding troubleshooting flows interactively. Emily’s source of truth, structured the way your team already thinks.