Design-partner preview for teams shipping with AI

Move fast without losing the why.

Synaura finds where decisions, roadmap, product claims, and customer evidence disagree — before the gap becomes rework. Then it keeps the approved context available to every team and AI agent.

By requesting access, you agree that Synaura may contact you about the controlled preview. See our Privacy Policy.

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Bring one real contradiction · Design-partner onboarding · Read-only by default

4D
Team · roadmap · market · agents
Read-only
Connections by default
MCP
Context where agents work
Human
Review before action
Synthetic product preview illustrative
4 clusters need review
Internal · Slack / Linear
“we should look at this next quarter”#prod-strategy · 8w · @marcus
“fhir validator silently drops malformed bundles…”#infra-eng · 6d · @priya
Roadmap · Linear
NW-2841 · alerting v2 · in progresspriority P1
— no SSO ticket present —despite 3 G2 mentions
External · G2 / Reddit
“SSO config is opaque — took 3 weeks of back and forth.”G2 · 2d · enterprise
“reporting flexibility is where they lose to Tebra.”r/healthIT · 5d · 24 ↑
Illustrative onboarding walkthrough

How a first scan unfolds.

Synthetic example A · Accounting firm

Morrison & Associates · 45 people

00:00Connected Slack workspace (12 channels, 3,400 messages)
02:15Extracted 31 client-handling procedures from #client-ops
04:30Mapped 8 people with tax expertise, 3 single points of failure
08:00Alert: Senior partner Sarah handles 40% of filing deadlines alone. If she's unavailable, 120 clients miss Q3 deadlines.
12:00AI assistants now serve all 300 clients using signed skill files — human approval is required before use.
Synthetic example B · SaaS startup

Velocity Labs · 85 engineers

00:00Connected Slack + GitHub (14 repos, 2,100 PRs)
03:00Extracted 18 architecture decisions from #eng-architecture
05:00Conflict: Team A's Claude decided Redis for caching. Team B's Cursor picked Memcached. Same service. Neither team knew.
05:01Conflict detected. Both decisions preserved. Escalated to engineering lead.
30:00Every new engineer's AI assistant already knows every architecture decision from day one.

Illustrative data and sequence. Scan time and findings vary by source volume and data quality.

See the full interactive demo →
Live · Synthetic · Northwind Health

What Synaura sees that your team doesn't.

In this synthetic walkthrough, a 200-person healthcare SaaS has just connected Slack, GitHub, Linear, Zendesk, G2, and Reddit. Here is what Synaura would surface.

streaming org_demo_northwind · 14:22Z
ClusterPatternIntExtARR ExposedStatus
fhir ingestion reliabilityINT_ONLY30—Latent risk
reporting customizationEXT_ONLY01$380KBlind spot
patient matching accuracyEXT_ONLY01$510KBlind spot
sso configurationEXT_ONLY01$150KBlind spot
hipaa audit trailEXT_ONLY02$610KBlind spot
real time alertingINT_LEADING21$280KDrift
ehr integration onboardingSYNCHRONIZED12$620KCovered
14 clusters · 4 misaligned · $1.94M ARR exposedClick any row · or press 2
How it works

Connect. Detect. Act.

01 · Connect
01

Hook up your stack.

Slack, GitHub, Linear, Google Drive, Gong, Fathom — plus G2 reviews, Reddit, marketing site crawl, and inbound webhooks for any custom source. OAuth where possible. Read-only by default.

02 · Detect
02

Run the Coverage loop.

Synaura builds the operating graph and runs the Signal Coverage loop continuously. The four-dimensional join surfaces gaps, drift, and latent risks — week one detects misalignments accumulating for quarters.

03 · Act
03

Prepare reviewed context.

Reviewable context packages for controlled MCP evaluation. Proof state is explicit wherever signature evidence is available. Draft specs and CS macro updates land in the alignment dashboard for human review.

Cold-start memory

Start with history, not a blank slate.

Connect the history you choose so the first graph starts with prior decisions, tickets, conversations, and documents. Backfill depth, speed, and coverage depend on source access and volume.

2025-05412
2025-071.2K
2025-092.4K
2025-113.8K
2026-015.1K
2026-036.4K
2026-057.9K
illustrative backfill · synthetic volumetiming varies
CAMP protocol preview

Context you can inspect, not just trust.

When AI agents act on company instructions, provenance matters: what changed, who approved it, and which evidence supports it.

CAMP is the protocol work behind Synaura's consistency and provenance model. Compiled skill artifacts can carry source references and an ML-DSA-65 signature for independent verification.

The product labels capabilities as live, preview, or planned. Security and compliance work is described by current status rather than implied certification.

Inspect the protocol preview →
protocol statuspreview
signature schemeML-DSA-65 · FIPS 204
artifact provenancesource references
distributionMCP-compatible
verificationpublic-key metadata
connectionsread-only by default
action controlhuman review
SOC 2 Type Iin progress · not certified
capability labelslive · preview · planned
security contactsecurity@synaura.ai
Built for B2B SaaS · 50–500

For the team shipping faster than it can align.

  • You ship in days, not weeks, because of agentic coding tools.
  • You have at least one engineer who is a single point of knowledge for a critical system.
  • You've shipped at least one feature in the last six months that turned out to be the wrong thing.
  • Your stack includes Slack, GitHub, Linear or Jira, and a customer support tool.
  • You read your G2 reviews and wish your roadmap reflected them faster.
  • You've ever said: “we're shipping fast but I'm not sure we're shipping the right thing.”
FAQ

Real objections.
Real answers.

Isn't this just a wiki?
No. Wikis store documents. Synaura builds a typed graph of people, decisions, processes, and signals across systems and detects when they disagree.
How is this different from Glean or Notion AI?
Glean and Notion AI answer “find me the doc.” Synaura answers “your roadmap and your customers don't agree.” Different question, different product.
How is this different from Productboard?
Productboard aggregates internal feedback and ties it to roadmap. Synaura adds external signals (G2, Reddit, app stores), marketing-language coverage, internal team awareness, executable signed skills, and latent risk detection.
Do you ingest our data into a model?
Connected tools remain the systems of record. Synaura stores source references and the content needed to build its graph and evidence trail. Retention, deletion, and export controls should be confirmed during onboarding for your deployment.
What is a “signed skill file”?
A versioned, structured procedure that can be prepared for SKILL.md, MCP tools, function schemas, or Markdown. Signature and public-verification availability are labeled explicitly in the controlled preview.
Why post-quantum signatures?
To avoid building new long-lived trust infrastructure on signature schemes that are not designed for a post-quantum future. ML-DSA is standardized in NIST FIPS 204; Synaura uses the ML-DSA-65 parameter set for signed artifacts.
Where does it run?
Synaura runs on Cloudflare Workers with Cloudflare-managed storage services. Data location, residency, and enterprise controls depend on the contracted deployment and should be verified during security review.
Can my agents call Synaura via MCP?
Yes. mcp.synaura.ai/{your_org} is your endpoint. Any MCP-compatible runtime (Claude Code, Cursor, etc.) can list, fetch, and execute your signed skills.
SOC 2 / security?
SOC 2 Type I work is in progress; Synaura is not currently certified. Read-only OAuth scopes are the default. Request the current security overview, control status, and data-flow details before production use.

Speed is useful.
Shared context makes it count.

Join the design-partner program with one real contradiction. We will trace the evidence, make the disagreement reviewable, and define the first credible finding together.

Request access → Book a 15-minute walkthrough →