Your competitors are moving. You're reading last quarter's report.
We build AI-powered intelligence systems that continuously monitor your competitive environment: product changes, pricing shifts, hiring signals, market narratives. Your strategy stays grounded in current reality, not stale data. This is a standalone research and intelligence service, not a marketing engagement. It serves strategy, product, and commercial teams across the business.
Competitive intelligence is broken at most companies.
You find out last
A competitor drops a new pricing tier or launches a feature you had on the roadmap for six months. You hear about it from a sales rep who heard it from a prospect. By the time it is actionable, the moment has passed. Manual monitoring is too slow and too inconsistent to catch what matters when it matters.
Research that's already outdated on delivery
Traditional market research is a snapshot. A firm spends eight weeks on interviews, synthesis, and packaging. You receive the deck ten weeks after the brief was written. The market has moved. You own an expensive document that describes a world that no longer exists.
Signal volume with no signal filtering
There is no shortage of information about your competitors. There is a severe shortage of relevant insight. News alerts, LinkedIn posts, job boards, G2 reviews, patent filings, conference talks. They all contain signals. Without a system to collect, filter, and interpret them, the volume is just noise that no analyst has time to process.
Strategy built on assumptions
When real-time intelligence is absent, strategy drifts toward gut feel and anecdote. Teams make positioning decisions based on what competitors were doing two quarters ago. Roadmap prioritisation reflects what you have heard, not what you have verified. The cost compounds quietly. Misallocated R&D. Missed positioning windows. Slow competitive responses.
A continuous intelligence system, built to run, not to gather dust.
We design and deploy automated monitoring infrastructure that tracks the signals that matter for your specific market, delivering structured insights on a cadence your team can act on.
Intelligence Scoping & Source Mapping
Week 1
We work with your strategy, product, and commercial teams to define the intelligence questions that matter most. Which competitors. Which market segments. Which product categories. Which signals are predictive of moves you care about. We then map every available data source (public and semi-public) that bears on those questions: job postings, pricing pages, patent databases, review platforms, regulatory filings, conference schedules, press coverage, GitHub activity, and more. The output is an intelligence taxonomy: a structured map of what we're watching and why.
Deliverable: Intelligence scoping document with competitor universe, signal taxonomy, and source map
System Design & Data Pipeline Build
Weeks 2-4
We build the monitoring infrastructure. Automated scrapers and API integrations for your priority sources. An AI processing layer that classifies and scores incoming signals against your defined intelligence categories. A structured database that stores enriched intelligence with full provenance. Alerting logic that routes high-priority signals to the right people immediately while queuing lower-priority items for regular briefings. Every system is designed for your specific market.
Deliverable: Deployed intelligence pipeline with monitoring dashboard, alerting configuration, and data dictionary
Intelligence Delivery & Analyst Layer
Ongoing
Raw signal collection is not intelligence. We add an analytical layer, either a human analyst on retainer or an AI synthesis model tuned for your market context, that turns incoming data into structured briefings. Weekly competitive digests. Immediate alerts for defined trigger events (competitor pricing change, major hire, product launch). Quarterly deep-dive analysis on market trajectory. Every output is formatted for the specific decision-maker who needs it.
Deliverable: Weekly intelligence briefings, trigger-based alerts, and quarterly market analysis reports
Intelligence Scoping & Source Mapping
Week 1
We work with your strategy, product, and commercial teams to define the intelligence questions that matter most. Which competitors. Which market segments. Which product categories. Which signals are predictive of moves you care about. We then map every available data source (public and semi-public) that bears on those questions: job postings, pricing pages, patent databases, review platforms, regulatory filings, conference schedules, press coverage, GitHub activity, and more. The output is an intelligence taxonomy: a structured map of what we're watching and why.
Deliverable: Intelligence scoping document with competitor universe, signal taxonomy, and source map
System Design & Data Pipeline Build
Weeks 2-4
We build the monitoring infrastructure. Automated scrapers and API integrations for your priority sources. An AI processing layer that classifies and scores incoming signals against your defined intelligence categories. A structured database that stores enriched intelligence with full provenance. Alerting logic that routes high-priority signals to the right people immediately while queuing lower-priority items for regular briefings. Every system is designed for your specific market.
Deliverable: Deployed intelligence pipeline with monitoring dashboard, alerting configuration, and data dictionary
Intelligence Delivery & Analyst Layer
Ongoing
Raw signal collection is not intelligence. We add an analytical layer, either a human analyst on retainer or an AI synthesis model tuned for your market context, that turns incoming data into structured briefings. Weekly competitive digests. Immediate alerts for defined trigger events (competitor pricing change, major hire, product launch). Quarterly deep-dive analysis on market trajectory. Every output is formatted for the specific decision-maker who needs it.
Deliverable: Weekly intelligence briefings, trigger-based alerts, and quarterly market analysis reports
Live intelligence infrastructure. Updated continuously.
Setup & Infrastructure (Weeks 1-4)
- Intelligence scoping document with competitor universe, priority signal categories, and source map
- Deployed monitoring pipeline covering all defined sources with automated ingestion
- AI classification and scoring layer calibrated to your market and intelligence priorities
- Monitoring dashboard with live signal feed, competitor profiles, and alerting controls
Ongoing Intelligence Delivery
- Weekly competitive briefings structured by competitor and market theme
- Real-time trigger alerts for high-priority events (pricing changes, major hires, product launches, M&A signals)
- Quarterly deep-dive reports on competitive positioning shifts and emerging threats
Strategic Support
- Monthly strategy call to review intelligence findings and adjust monitoring priorities
- Ad hoc research requests (up to 4 per month) for specific competitive questions
Intelligence informs strategy. It doesn't replace it.
This engagement builds and operates your competitive intelligence infrastructure. Adjacent needs are scoped separately.
Go-to-market strategy or repositioning
Intelligence will show where competitors are vulnerable and where your positioning is weak. Deciding what to do about it (messaging changes, pricing adjustments, market entry sequencing) is a strategy engagement, not an intelligence one.
Primary research (customer interviews, surveys)
Our system focuses on publicly available and semi-public signals. Primary research to validate hypotheses or gather direct customer or prospect perspectives is a separate engagement.
Internal data integration
If you want intelligence signals fused with your internal CRM data, product analytics, or win/loss records, that integration is scoped and priced separately based on your stack.
Is this the right fit? (This is a research service, not a marketing service.)
Right for you if
- You operate in a market that moves fast (SaaS, fintech, D2C, healthcare tech) where a competitor's pricing change or product launch in Week 1 can show up in your churn numbers by Week 6.
- Your strategy, product, or commercial teams are making decisions based on intelligence that's months old, and you've lost at least one significant opportunity because you found out too late.
- You have the internal capacity to act on competitive insights but not the infrastructure to collect and synthesize them at the speed and volume the market demands.
Not right if
- You're in a slow-moving market where competitive positions are stable across years. The ROI on continuous monitoring won't justify the investment.
- You need a one-time market research report, not an ongoing system. A point-in-time project is a better fit, and we can scope that separately.
- You don't have a decision-maker who will act on intelligence findings. A system that produces insights nobody reads is a cost, not an asset.
What this looks like in practice.
Problem
A Series B HR tech company was losing deals to two competitors without a clear pattern. Win/loss data was anecdotal. The sales team attributed losses to price; the product team attributed them to features. The CEO suspected both were wrong.
What we did
Built an intelligence system monitoring both competitors across product changelog pages, G2 and Capterra reviews, job postings, LinkedIn content, and pricing page variants. Within six weeks, the system surfaced a consistent pattern: one competitor had quietly repositioned toward mid-market enterprise with a new implementation services wrapper, changing the buying committee dynamics in exactly the deals the client was losing.
Outcome
The commercial team adjusted its enterprise pitch to address implementation risk before it became an objection. Win rate in the affected deal segment improved 18 percentage points over the following quarter.
Problem
A digital lending platform needed to monitor four competitors in real time for pricing changes and product launches, but had no systematic way to do so. A competitor had launched a new credit product two months earlier, and the team found out only when a journalist called for comment.
What we did
Deployed monitoring across competitor rate pages, app store listings, play store reviews, regulatory filing databases, and press feeds. Set up trigger alerts for any change in rate structure, product terms, or marketing messaging within defined thresholds. The alert latency for a detected change went from weeks to under four hours.
Outcome
The product team was able to respond to a competitor rate cut within 48 hours of detection rather than two weeks. That window had historically cost them disproportionate application volume in the week following a competitive rate change.
Problem
A premium D2C brand was struggling to understand whether its price premium was sustainable as new entrants crowded the category. Market research was expensive and infrequent. The team had no systematic way to track how competitors were pricing, promoting, or positioning across channels.
What we did
Built a monitoring pipeline covering competitor product pages, promotion calendars, paid ad libraries, influencer partnership activity, and customer review sentiment. Generated a weekly pricing and positioning digest that tracked changes over time with trend analysis.
Outcome
Identified that two competitors were discounting heavily in a pattern that preceded a funding-driven growth push, giving the client eight weeks of lead time to adjust its own promotional calendar and protect margin during what would have been an expensive defensive response.