AzImuth — IR Intelligence Platform
A platform built for IR teams that want to know if their story is landing, whether their outreach is producing shareholder outcomes, and exactly where analysts are getting the narrative wrong.
The Real Problem
You have the filings. You have the transcripts. You have the ownership reports. You run the roadshows. What you don't have is a continuous loop between what you're saying and how the market is actually hearing it — or any systematic way to know whether any of it is working.
The gap isn't effort. Most IR programs are doing the right things. The gap is measurement. Which investors are actually moving after you meet them? Is your narrative landing differently than you think? Are your analysts modeling you correctly, or are there specific divergences costing you on price targets and consensus? Is the perception study you ran two years ago still accurate?
Those aren't data questions. They're signal questions. And existing tools — data terminals, CRM platforms, annual studies, generic AI — aren't built to answer them.
Use Cases
Each use case addresses a distinct problem. Find yours.
"We had a great roadshow. 28 meetings, strong conversations." That's activity. What actually changed?
Most IR teams report what they do — meetings attended, conferences participated in, investors contacted. Almost none can answer the board's real question: which of those relationships resulted in an investor actually buying shares?
This platform logs every investor touchpoint and auto-correlates each investor's meeting history against their ownership position, quarter over quarter. You can aggregate results by bank, by event type, by outreach channel, and show exactly which parts of the program are producing outcomes and which aren't.
By the time a misperception shows up in the stock, it's already cost you. Annual studies are expensive, infrequent, and stale on arrival.
Investor perception is one of the highest-leverage variables in IR — and one of the least continuously monitored. Most IR teams run a perception study once a year if they're fortunate, then operate on anecdote and instinct for the other 11 months.
This platform makes perception measurement continuous, on-demand, and genuinely intelligent. Survey questions are designed by AI from your own documents, not templated by a research firm. Results track over time, so you can see whether narrative changes are actually improving how investors hear your story.
The gap between your story and the right version of your story for each audience is where the valuation discount lives.
Most IR teams have one narrative. Sophisticated investors — long-only growth funds, value managers, GARP strategies, activists — evaluate companies through fundamentally different lenses. A single undifferentiated message leaves money on the table.
The platform's 6-stage narrative builder synthesizes your company documents and management interviews into a full institutional narrative, then generates tailored talking points by investor type. The adversarial pressure testing stage — where AI challenges your story with the toughest likely investor questions — finds the weak points before investors do.
You find out at the roadshow when they ask a question that reveals a model assumption you didn't know was wrong. That's too late.
Analyst model divergence from management guidance is one of the most undermonitored risks in IR. EPS estimates miss. Margin assumptions differ. Capital allocation gets modeled incorrectly. Most IR teams know divergence exists — they just don't have a systematic way to identify exactly where, by analyst, before it affects price targets and consensus.
The platform extracts EPS estimates and key line items from every uploaded analyst report, compares them automatically against your guidance, and surfaces per-analyst divergence with recommended outreach actions. It also analyzes narrative tone across your coverage universe, so you know which analysts are constructive, which are skeptical, and which are misunderstanding the core story.
A 45-minute conversation with a long-only fund manager contains signal that should be shaping your next earnings script and roadshow prep. Instead, it lives in a notes file no one reads again.
IROs and management teams have hundreds of investor conversations every year. Notes get taken sometimes. Recordings get stored occasionally. Themes, repeated objections, and evolving investor concerns never get synthesized. The next roadshow prep starts from scratch because institutional memory doesn't compound — it disappears.
The platform logs every investor touchpoint, transcribes and summarizes meetings with AI, and identifies repeated questions, emerging objections, and narrative gaps across the full meeting history. Every roadshow prep starts with an actual brief built from real investor conversations.
Why Existing Tools Fall Short
The gap isn't data. It's connected intelligence — grounded in your specific company, measuring outcomes, and improving over time.
Why This Is Different
How It Works
Upload your filings, earnings transcripts, analyst reports, ownership data, and meeting notes. The platform indexes everything and uses it as the grounding layer for every analysis. Your data stays yours.
The platform surfaces perception gaps, narrative misalignments, analyst model divergence, investor engagement patterns, and meeting intelligence — connecting threads across your entire IR program.
Every output is actionable: tailored talking points, effectiveness reports, perception results, analyst outreach recommendations, board-ready analytics. Built to be used, not just read.
Request a Demo
Most IR teams are doing the right things. What they're missing is a measurement layer that connects activity to outcomes, perception to messaging, and analyst models to company guidance. That's what this platform is built for.
Schedule a Demo