CONTEXT-AWARE AGENT FRAMEWORK

build agents
that think in context.

Zanora is AI-native software infrastructure. Our stateful agent framework gives developers production-ready building blocks — starting with the PM PRD Agent.

Join early access →Request a demo GitHub (soon)

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Stateful by design

Context persists across turns, tool calls, and restarts

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Token-efficient

Only what matters stays in context

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Production-ready

Vertical templates to ship in hours

→ ingesting context...▌

THE FRAMEWORK

Agents that actually remember what matters

Most frameworks bolt memory on as an afterthought. Zanora is designed around it — stateful, opinionated, and production-ready.

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Stateful Agents

Every agent carries a memory graph that persists across turns, tool calls, and restarts. No context-rebuild boilerplate.

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Token-Efficient Memory

Selective compression keeps prompts lean. The framework decides what to retain, summarize, or drop.

◎

Tool Orchestration

Declarative tool definitions with structured output validation. Compose multi-step pipelines without glue code.

◻

Vertical Templates

Production-ready agent templates for real workflows — PM PRD Agent is first. More verticals coming.

HOW IT WORKS

Ship your first agent in an afternoon

01

Define your agent

const agent = new ZanoraAgent({
  tools: [searchDocs, createTicket],
  memory: 'selective',
  template: 'prd-agent'
});

Declare tools, memory strategy, and optionally start from a vertical template.

02

Run a session

const result = await agent.run({
  input: userMessage,
  context: existingDocs,
  sessionId: 'sprint-42'
});

Sessions persist state automatically. Resume any session with its ID.

03

Inspect memory

agent.memory.snapshot();
// → { retained: [...],
//     compressed: [...],
//     dropped: [...] }

Full observability into what the agent remembers and why.

FIRST TEMPLATE

PM PRD Agent

The first production-ready template built on Zanora. For PMs tired of writing PRDs from scratch — and engineers tired of receiving incomplete ones.

→Ingests meeting notes, Slack threads, Jira tickets

→Produces structured PRDs with acceptance criteria

→Maintains context across PRD revisions

→Asks clarifying questions only when needed

→Outputs in your team's template format

Try the PRD Agent →

prd-agent · session_2847
▌

VISION

One framework.
Every vertical.

The PRD Agent is the first proof. We're building the foundation for AI-native software across every knowledge-work vertical.

TODAY

◻Context-Aware Agent Framework

◻PM PRD Agent template

◻Developer early access

NEXT

◻Sales Agent template

◻Support triage Agent

◻Agent observability dashboard

FUTURE

◻Full vertical agent library

◻Agent-to-agent orchestration

◻Hosted agent runtime

* No committed delivery dates — we ship when it's ready.

FAQ

Common questions

LangChain and LlamaIndex are broad, flexible toolkits. Zanora is opinionated — it makes specific architectural choices (stateful memory by default, structured tool contracts, vertical templates) so you spend less time on plumbing. If you want maximum flexibility, LangChain is fine. If you want to ship a production agent fast, Zanora is for you.

Yes. Zanora works with any LLM provider through a standard interface. We have first-class support for OpenAI and Anthropic, with LiteLLM integration to cover the rest of the landscape.

Agents typically dump everything into context, burning tokens and hitting limits. Zanora's memory layer selectively compresses, summarizes, or drops context based on recency and relevance — so prompts stay lean and costs stay predictable.

We're onboarding early access developers now. Join the waitlist and we'll reach out when your spot opens. We're keeping the initial cohort small so we can give real hands-on support.

TBD — we're not charging for early access. We'll publish pricing before GA. Reach out if you have specific constraints you'd like us to design around.

GET STARTED

Join the developer waitlist

We're onboarding a small cohort of early developers. Get access to the framework and the PM PRD Agent before public launch.

build agentsthat think in context.