Signal in the noise. From the first customer question to the merged fix.
Zygnal is an AI-native platform for support and engineering — living help docs, a learned support memory, tickets that link to your code, and an in-product drawer. One place where customer questions, support work, and engineering fixes all see each other.
Every resolved ticket becomes a captured insight. Insights become new articles and engineering fixes. Engineers triage tickets with code in context — soon, from inside their IDE. The loop closes.
Hosted in Sydney (ap-southeast-2). Multi-tenant from day one. Plugged into your code, not just your help desk.
Click Profile → Security, then Reset password. You'll get an email link that lasts 30 minutes.
Support tooling makes you choose. Zygnal does not.
Most teams duct-tape five tools together: a help-doc CMS, a ticket system, an AI chat add-on, a wiki for "things we have learned," and a project tracker the engineers actually open. Each one is partly aware of the others. None of them close the loop, and none of them know about your code.
Help docs go stale
You wrote them six months ago. The product changed twice. Now they're wrong, and customers find the wrong answers before they find your team.
Hard-won knowledge gets lost
Every resolved ticket teaches your team something. Most of that learning lives in someone's head, in Slack threads, or in a Jira comment nobody will read again.
AI without context is useless
Generic AI chatbots start cold every time. They do not know your product, your customers, or what your team has already worked out. So they hallucinate, or punt to human.
The fix loop never closes
Customer reports a problem. Engineer fixes it. Six weeks later, same question from a different customer. Nobody updated the docs. Nobody told marketing. The cycle repeats.
Four parts, one loop.
Your customers get a helpful AI right inside your product. Your support team gets tickets routed and triaged with full history. Your engineering team gets the ticket, the linked code, and the knowledge fed back as fixes and docs — and, over MCP, from inside their IDE.
Help docs that stay current
Markdown sources, AI-polished, continuously refreshed. Edit by hand or by source — Zygnal keeps a diff against the original. Each article carries page routes, freshness scores, and a "last validated" date so you always know what is fresh.
A learned support memory
Every resolved ticket becomes a structured insight: symptom, cause, resolution. Insights cluster into patterns. Patterns become new help articles and product-improvement candidates. The knowledge grows automatically.
Tickets, not a black box
First-class tickets with severity, priority, SLA, sprint backlog, and GitHub branch + PR linking. Threaded replies. Email-to-ticket via Mailgun. Sync with Jira. The canonical record lives with you, not in a vendor silo.
An in-product drawer
Embeddable widget your customers see inside your SaaS app. Contextual help, the Sage AI agent grounded in your knowledge, ticket creation, file uploads with Vision OCR. HMAC-signed identity — no extra signup.
The closed loop:
Customer asks → drawer answers from KB → if not, opens ticket → AI triages with code from the linked repo → engineer ships a fix as a PR → merge updates the ticket, drafts the article, closes the loop with the customer → next customer finds it themselves.
The support platform that talks to your code.
Most "support tooling" treats the engineering hand-off as someone else's problem. Zygnal treats it as the point. Tickets link to repos. AI reads the code. Your IDE sees the prep. Fixes feed the knowledge base.
Or, more bluntly: prep is the bottleneck, not coding speed. Zygnal closes the prep gap.
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Zygnal MCP server for your IDE
Connect Claude Code, Cursor, or Windsurf to Zygnal over MCP. Your editor pulls the full ticket — thread, KB, past resolutions, and repo file + code search — and can log the resolution back, all without copy-pasting context.
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In-ticket AI with code in context
When triaging, Sage reads files, searches code, and walks the directory tree of the linked repo — surfaced inline as the conversation happens. Every read is audited.
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Branch + PR linking on every ticket
One click creates a branch from your default base. PRs that reference the ticket update its status automatically via webhook. The link survives re-titling, re-assignment, and merging.
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Repository access, scoped per product
Link repositories to a product; code access stays scoped to that product's repos, so your support team can't read code they shouldn't. Every call is recorded.
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Sprints, severity, SLA
First-class sprint backlog with drag-to-rank, per-product calendars, and breach tracking. Engineering capacity sits next to support load, not in a separate tool your team forgets to open.
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Fix-landed, loop-closed
When the PR merges, Zygnal flags the originating ticket and drafts the "it's fixed" reply to the customer and the resolution write-up. You review and send.
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Code indexing for semantic search
Embeddings over your linked repos so the AI finds relevant code by intent, not just keyword — another retrieval surface alongside articles and resolution insights.
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Two-way PR ↔ ticket sync
PR review comments mirror back onto the ticket thread, and branch protection can key off ticket state — so the conversation stays in one place.
Engineer's loop:
Customer reports a bug → support triages with AI, attaches the relevant code → engineer opens the ticket in their IDE via MCP → fix goes out as a PR → merge updates the ticket, drafts the article, closes the loop with the customer.
Everything support, nothing extra to wire up.
The features below are live in the platform today, in active internal use across our own product suite.
Sage, the AI agent
One agent across the drawer and every ticket. In the drawer it answers from your docs and past resolutions with cited sources and can open a ticket; on the support side it triages, drafts replies, and reads code. Grounded in your knowledge — it never starts cold.
In-product drawer
Embeddable widget with HMAC-signed identity, JWT-scoped chat, contextual help by page route, ticket creation, and file uploads with Vision OCR on screenshots. One snippet to install; no extra signup for your customers.
Hybrid retrieval
Full-text + semantic search, weighted and tunable. Markdown-aware chunking preserves heading context. Per-tenant + per-product partitioning — no cross-product bleed.
Insight capture & cluster mining
Every resolved ticket is summarised into a structured insight. Insights cluster to surface emerging patterns, seed new article drafts, and flag product fixes — not just workaround docs.
Anomaly detection
Isolation-forest models watch ticket signals — volume spikes, unusual subject clusters, severity shifts — so you see issues before they snowball.
Weekly retrospectives
Per-space summaries: volume and deltas, the week's anomalies, top recurring patterns, and a prioritised "fix these" list drawn from cluster improvement drafts. In-app and in a Monday digest.
Sprints & engineering workflow
First-class sprints with drag-to-rank, a configurable kanban per workspace, severity and SLA. One-click branch + PR linking, with PR events updating ticket state via webhook.
Code access + MCP server
Link repos per product; Sage reads files, searches code, and walks the tree — scoped and audited. The Zygnal MCP server is live: connect Claude Code, Cursor, or Windsurf to pull ticket context straight into your editor.
Integrations that already exist
Jira import + webhook, GitHub branch/PR linking and code access, Slack notifications, inbound + outbound email-to-ticket, and federation to pull articles from your existing help system. Nothing has to migrate on day one.
Per-tenant SLA engine
Business calendars per tenant, override profiles per product or per customer, breach tracking built in. SLA is a first-class citizen, not a stitch-on report.
ROI you can see
Deflection rate, tickets resolved, MAU, and SLA performance surfaced live in the admin — the evidence that the loop is working, not a line item.
Audit log + multi-tenancy
Every mutating action is audit-logged via middleware. Tenant + product isolation enforced at the query layer, with row-level security on the roadmap.
Plugged into the tools you already run.
Zygnal slots into your stack instead of replacing it. Keep Jira for engineering, your repos on GitHub, your alerts in Slack — Zygnal ties them to the support loop. All live today.
Jira
Two-way: import resolved tickets (years of history) and ingest live events by webhook. Field discovery per instance.
GitHub
Link a branch and PR to any ticket; PR events update its state. Scoped, audited repo access for the AI.
Slack
Notifications to the channels you choose — dev-ticket requests, raises, and completions. Connect in a click.
Inbound email threads into tickets; replies from Zygnal go back out as email. Your customers never see a portal change.
MCP — Claude Code, Cursor, Windsurf
The Zygnal MCP server exposes ticket context, KB, past resolutions, and code search to your IDE-connected AI.
Federation
Pull articles from an existing help system for unified search before you migrate anything. One-way, non-destructive.
Anthropic + OpenAI
Claude runs the agent, triage and content; OpenAI embeddings power search. Called directly — your data is not used for training.
KernelService (optional)
Route the drawer agent through KernelService when you want deeper cross-system actions. Off by default.
Flat price per workspace. Unlimited seats.
One meter — monthly active users who actually use your drawer. Not per-seat, not per-resolution. Unlimited staff, unlimited spaces, AI included. Start free; annual prepay saves 20%.
Free
Up to 250 monthly active users
Everything you need to launch: KB, tickets, the drawer, and the Sage AI agent — capped, with a "Powered by Zygnal" badge.
- Unlimited staff seats
- 1 space
- AI drawer agent (Sage)
- Help portal + tickets
- "Powered by Zygnal" badge
Core
Up to 1,500 monthly active users
The full platform for a growing product: unlimited spaces and seats, the complete AI agent, branded portal, badge off.
- Everything in Free, plus:
- Unlimited spaces
- Full AI agent — no cap
- Branded help portal
- Badge removed
- Email support
Team
Up to 6,000 monthly active users
Add the closed-loop intelligence: cluster mining, product-improvement drafts, and anomaly detection on your ticket signals.
- Everything in Core, plus:
- Cluster mining + improvement drafts
- Anomaly detection
- Deeper insights + retrospectives
- Priority support
Scale
Up to 20,000 monthly active users
For larger reach and tighter controls: custom SLAs, audit-log streaming, a lifted fair-use ceiling, and dedicated support.
- Everything in Team, plus:
- Custom SLA
- Audit-log streaming
- Lifted fair-use ceiling
- Dedicated support
Bigger than Scale?
Enterprise — 20,000+ MAU, custom terms, and the security work as it lands.
Included on every paid plan
- Unlimited staff seats — every hire is free
- Unlimited spaces — external products and internal service desks
- The Sage AI agent, in the drawer and on every ticket
- Knowledge base, hybrid search, branded help portal
- Tickets, SLA engine, sprints, GitHub branch + PR linking
- Jira import + webhook, Slack, email-to-ticket, federation
- The Zygnal MCP server for Cursor / Claude Code / Windsurf
- Full multi-tenant admin app + audit log
What's a monthly active user?
One unique end-user who actually uses your drawer in a calendar month — asks the AI, searches your docs, or opens a ticket. Counted once per workspace, however many spaces or sessions they have. Your staff are never counted, and anonymous traffic on your public help site is free.
You see the live number in your admin — no surprises. Prices are USD; Stripe shows and charges in your local currency, with GST/VAT handled automatically.
Built for B2B SaaS, hosted where you'd expect.
Zygnal runs our own product suite in production. The posture you'd want for your customers' data is the one we hold for ours.
Australian data residency
Hosted in AWS ap-southeast-2 (Sydney). Data does not leave the region by default. Multi-region is on the roadmap for larger deployments.
Multi-tenant from day one
Tenant + product isolation enforced at the query layer. Postgres row-level security and per-tenant KMS keys are on the roadmap for Scale.
Audit log on every mutation
Middleware-driven audit logging on all writes. Stream to your SIEM on Scale. Nothing happens in the system that is not recorded.
HMAC-signed drawer identity
The in-product drawer authenticates customers via HMAC-signed boot tokens issued by your backend. Your drawer, your identity, no extra signup.
SOC 2 on the roadmap
SOC 2 Type II, SSO/SCIM and audit-log streaming are committed for larger deployments. Compliance posture is being built deliberately, not retrofitted.
Vendor-independent ticket data
Tickets and resolutions are first-class records in your tenant. Federation is one-way pull from external sources. You can leave; your knowledge comes with you.
Common questions.
Is Zygnal generally available?
How does pricing work — what is a monthly active user?
What can the AI actually do?
How does the in-product drawer authenticate users?
How does Zygnal work with our existing Jira, GitHub, Slack and email?
Is this just for support teams, or also for engineers?
How does the AI access code without leaking it?
Can I use it for internal support too — IT or HR service desks?
Where is data hosted, and how is AI used?
Can we self-host?
How are SLAs handled?
How do I get started?
Start free today.
Create a workspace in minutes — no credit card. Embed the drawer, add your docs, and watch the support-to-engineering loop close.