Too much noise
Competitors ship pages, posts and pricing tweaks every week. Most of it is a new banner or a reshuffled menu. Someone still has to look.
Competitor & market intelligence
Market intelligence
with receipts.
We build monitors that watch your competitors every day, keep only what really changed, and answer every question with a verbatim quote, a source link and a date. Your team reads it in Slack. Your AI agents query it directly.
agent → monitor
› What did Vendor A change in the last 30 days?
- CLAIM
- Vendor A now positions itself for regulated enterprises, not developers.
- QUOTE
- “Built for security teams in regulated industries.”
- SOURCE
- vendor-a.example/platform · first seen 2026-10-08
- NOTE
- Interpretation: the homepage headline changed the same week. Not stated as a strategy shift.
- GAP
- Enterprise pricing: not in the scraped data.
The problem
Everyone watches the market. Few can prove what they saw.
Competitive intelligence usually fails in one of three ways. We built our approach around all three.
Summaries you can't check
AI tools happily summarise a market. Then one confident sentence turns out to be invented, and nobody trusts the next one.
Insight that goes stale
The quarterly deck is out of date the day it ships. By the time a change reaches sales, the competitor has moved again.
What we build
A living record of your market
Four parts that work together. Start with one and add the rest as you go.
Website & blog monitor
Every competitor's site, blog and press page, checked daily. New, changed and removed pages get flagged with a one-line note. Cosmetic edits are ignored.
LinkedIn signal monitor
Daily collection of the company and people accounts that matter. Posts are scored for relevance, and the ones worth reading land in your Slack.
Claim extraction
Positioning, target buyer, products, pricing, customers, partners. Each one is pulled out as a structured claim with its quote, its link and the date it first appeared.
Agent access over MCP
Your AI assistants query the record directly. Ask what a vendor said in the last 30 days and get a dated, cited answer. The citation rules come built in.
How it works
From raw pages to answers you can cite
The same pipeline runs every day, without anyone touching it.
- 1
Collect
A scheduled run fetches each source directly. It falls back to a scraping network when a site blocks it, and to a headless browser for heavy pages.
- 2
Filter
Pages are normalised and fingerprinted. Dates, banners and menus don't count as change. An unchanged page is noted as seen again, never stored twice.
- 3
Extract
Real changes are turned into structured claims. Each one keeps its verbatim quote, its source and the date it was first seen.
- 4
Serve
People get digests in Slack. Agents get the same evidence over MCP. Failed runs alert us before you notice.
Evidence first
Built for people who have been
burned by AI before
We provide the evidence layer. Your team and your systems do the reasoning on top of it. Three rules hold for every answer the system gives, whether a person or an agent is asking.
Quote, link, date. Every time.
No fact without the words it came from, the page it was on and the day it first appeared. If you can't click through to it, we don't say it.
Interpretation is labelled
When a model summarises or connects dots, the text says so. You always know which sentence is evidence and which one is a reading of it.
Gaps are stated, not filled
If the data doesn't cover a question, the answer says “not in the scraped data”. A tool that isn't ready says so instead of guessing.
Case study
An AI-security vendor in a crowded market
The market moves weekly and every rival claims the same things. The team needed to know who said what, and when, without trusting a summary nobody could check.
What we set up: a daily LinkedIn monitor with AI scoring and Slack reports, then a website and blog monitor covering their closest competitors. It extracts claims into the client's own database.
How they use it: their AI assistants connect over MCP and pull vendor briefs and raw evidence on demand. Every line in a brief traces back to a quoted, dated source page.
Figures as of October 2026, first days of operation.
- competitors tracked from day one
- 5competitors tracked from day one
- pages under daily watch
- ~400pages under daily watch
- claims extracted, each sourced
- ~2,500claims extracted, each sourced
- runs, with alerts on any failure
- Dailyruns, with alerts on any failure
Working with us
Start small. Keep what you build.
We begin with a scoped pilot and grow it from there. Everything we build runs on your side.
Pilot
A handful of competitors, their websites and blogs, and agent access. Live within days, on a fixed scope and a fixed price.
Expand
More vendors, LinkedIn pages and key people, and weekly “what changed that matters” digests for the team.
Run
We operate and monitor the pipeline. You get the evidence, and the system keeps getting better as your questions sharpen.
- Data lives in your own database
- Running costs on your own accounts
- Every component swappable, no lock-in