Market intelligence
Sigblaze tracks your market, competitors, and customers to uncover what matters. Get evidence-backed insights and clear recommendations, so you know what changed and what to do next.
Private alpha. Pricing is not set.
The Sigblaze home screen. Synthetic demo data with fictional companies and sources.
What changed, what to do next
When a watchlist check finds a difference, Sigblaze raises a signal with the before and after, an importance rating, a confidence label and the snapshots behind it.
$49 per seat per month
Pro plan, meridian.example/pricing
$59 per seat per month +20%
Pro plan, meridian.example/pricing
Sigblaze creates drafts for you to review. Nothing is sent or published automatically.
Products
Research, Signals, Monitor, Brief and Ask all read from and write to the same stored sources, claims, insights and signals.
Turn a question into a bounded plan, stored sources, single-statement claims and insights.
Explore ResearchSee pricing, product, positioning and customer changes with the evidence, an importance rating and a confidence label.
Explore SignalsWatchlists re-check competitor pages and searches on a schedule and keep every snapshot.
Explore MonitorA daily, weekly or monthly digest of what changed, why it matters and what to do.
Explore BriefAnswers come from stored evidence, with citations. When there is none, Ask says so.
Explore AskEvery product writes to and reads from one graph, so any signal, insight or action can be traced back to its sources.
From change to action
One synthetic example, followed through four steps. Each step is stored and links back to the one before it.
Add pages and searches to a watchlist. The first check is a baseline. Every later check is compared with the last stored snapshot, and a real difference becomes a signal with the before and after.
Retrieved pages are stored with their type and retrieval date, then split into single-statement claims. Evidence can support, contradict or contextualise a claim. When sources disagree, the claim stays contested until a reviewer decides.
meridian.example/pricing
“Get your whole team live in a day. Per-seat pricing, 10-seat minimum.”
An insight links to the claims behind it and carries a confidence label and its freshness. Once a person approves it, it can become a battlecard, a positioning draft, a campaign direction or a report. Each action keeps a trace back to its insight.
Questions such as “What changed this week?” are answered from stored claims, insights and signals, with citations. When the evidence is missing, Ask says so and offers to start a research run.
What changed this week?
Three things were detected. The one that matters most: Meridian raised its Pro price from $49 to $59 per seat [SG-002, C-030]. Complaints about manual portal migration also increased [SG-004]. Tallyhouse added a Slack integration [SG-005].
Turn that into a battlecard against Meridian.
Battlecard drafted from approved insight I-007, with the price change cited. It stays a draft until you review it.
What do we know about Meridian onboarding?
Meridian advertises onboarding in a day [C-014, S1]. Two agency-side sources report multi-week migrations [C-015, S2, S3], and a July changelog entry notes a new CSV import that may have shortened this since [S4]. The evidence is contested.
What is Meridian's customer churn rate?
The stored evidence does not cover this. No claim in the workspace addresses churn.
Comparison
Chat tools suit one-off questions. Recurring research needs saved context, stored sources and something that keeps watching.
| Topic | One-off AI chat | Sigblaze workspace |
|---|---|---|
| Context | Re-explained in every chat | Saved workspace context, reused by each run |
| Sources | Links in a transcript, if any | Stored with type and retrieval date |
| Claims | A prose summary | Single statements linked to their evidence |
| When sources disagree | Often blended into one answer | Kept visible, and the claim stays contested |
| Noticing a change | Only when you ask again | Watchlists compare snapshots and raise signals |
| Weekly digest | You write it | A brief built from stored signals |
| Review | None | A person approves or rejects before reuse |
| Tracing an action | Not kept | Action to insight to claims, signals and sources |
Who it is for
Keep a separate workspace for each client and cite the source behind every recommendation.
For agenciesTurn incomplete client context and scattered research into recommendations you can defend.
For fractional teamsKeep competitor claims, sources and contradictions in one place, and get a signal when a competitor changes a page.
For SaaS teamsMethod
A reviewer can inspect the chain behind any conclusion in Sigblaze, including the changes it detected.
Each source is saved with its type, origin and retrieval date.
Evidence is labelled as supporting, contradicting or contextual.
A contested claim is not averaged into one confident answer.
A signal comes from two stored snapshots. A model can help word it but does not decide that something changed.
A model proposes. A person approves or rejects insights and actions before they are reused.
Each run and check records the context version and the sources it used.
Current status
Both lists come from one capability registry, so this page cannot promise more than the product does.
FAQ
Sigblaze is a market intelligence product. It researches your market, competitors and customers, checks them again on a schedule, raises a signal when something meaningful changes, and turns reviewed evidence into actions for marketing, sales, product and strategy. Sources, claims, contradictions, insights and signals are stored in the workspace, so the next question starts from what is already known.
Boutique B2B agencies running research for several clients, fractional CMOs and GTM consultants, B2B SaaS teams, and founders or product marketers who research competitors and markets on a recurring basis.
General AI tools are good for one-off questions and exploration. Sigblaze is built for recurring team research: it stores workspace context, keeps sources and claims, shows contradictions, preserves lineage and lets a team reuse approved intelligence in later research and actions.
You state a research goal, and the product turns it into a bounded plan of tasks and queries. Each task inherits the workspace's company, product, ICP, market and competitor context, so one vague prompt does not have to carry everything.
A claim is one factual statement extracted from a source. It stays linked to the evidence that supports, contradicts or adds context to it.
The disagreement is kept. A claim with contradicting evidence is shown as contested, and the system does not silently pick a preferred fact.
An insight is an interpretation written from stored claims and evidence. It keeps the claim relationships, confidence and freshness that produced it, and a person reviews it before it is reused.
Yes. Ask answers from the workspace's stored context, claims, insights, signals and sources, including what you approved or rejected, and it can answer questions such as “what changed this week?”. When the stored evidence is not enough, it says so instead of presenting general model knowledge as workspace evidence.
Sigblaze is built for agencies, fractional GTM teams and B2B SaaS teams that research the same markets on a schedule. Pricing is not set.
