Silo · privacy-first CDP
Pharma went digital.
Its analytics stack didn’t.
Silo is the privacy-first CDP with an AI analyst baked in — built in Canada, for regulated brands that need every number signed off.
Shipped monthly · Canadian residency · No hallucinations
Monthly report
[Brand]
2026-03-01 → 2026-04-01
Key Insights
- · 91% of quiz respondents don’t know their hemoglobin level.
- · HCP resource downloads up 34% month-over-month.
- · Patient-portal logins concentrate on Tuesday mornings.
- · 89% of raw events survived filtering — exceptionally clean traffic.
Primary outcome rate
17.6%
Data quality
487 of 2,350 events · 21% human
Running live, every month
- Brand 1 — placeholder pending approval
- Brand 2 — placeholder pending approval
- Brand 3 — placeholder pending approval
- Brand 4 — placeholder pending approval
- Brand 5 — placeholder pending approval
- Brand 6 — placeholder pending approval
Act 1 · Problem
The shift is already here
Pharma brand sites look like any other web property to the tools measuring them. They aren’t.
Patient and HCP audiences now arrive through the same surfaces as any consumer brand — organic search, paid media, referral, portal login. The measurement stack underneath them was built for consumer commerce, not regulated health. The numbers below come from 33 monthly reports shipped across eight live Canadian pharma brands between May 2025 and April 2026. They describe what actually shows up in the pipe before anything is filtered out.
79%
share of raw events on a typical Canadian pharma site that are bots, internal traffic, staging, or test data.
Silo aggregate, 33 monthly reports, May 2025–April 2026
21%
of 2,350 raw events on a patient-advocacy site in one recent month, the share that were real human traffic.
Silo, Canadian patient-advocacy brand, March 2026 report
2–3 weeks
current turnaround for one brand’s monthly analyst-written report at most agencies.
Internal benchmark, multi-agency pharma practice, 2025
What’s missing
Every role that touches a pharma brand’s numbers is working around the same three gaps.
Compliance teams reject dashboards they can’t defend, because vanilla GA4 counts bot traffic, staging domains, and the team’s own QA sessions as real visitors. Brand managers stop reading monthly reports full of page views and bounce rates, because none of those answer the only question that matters: did the resource get downloaded, did the HCP log in, did the patient request more info. Agencies spend two to three weeks per brand per month hand-writing reports that won’t survive a legal review — at $80,000 to $150,000 a year of analyst time, per brand. The behaviour is mainstream. The framework is missing.
Act 2 · Product
Meet Silo
Silo is a privacy-first CDP for regulated brands — event capture, routing, and outcomes reporting in one Canadian-residency stack. One SDK replaces Segment across every brand site; one AI Report Engine turns the captured events into the monthly report your legal team can sign.
How it works
Filter the pipe, then let the AI write.
Every GenAI analytics product on the market plugs into a warehouse that’s already full of bots, staging traffic, and internal sessions, and then produces “insights” on top of that garbage. Silo inverts the order. Events are filtered at the source — PII stripped before they leave the browser, bots and internal traffic classified server-side, staging and test data removed by rule, identity reconciled across anonymous-to-identified transitions — so the data the AI sees is already defensible. Because the taxonomy is known and the pipeline is governed, the Report Engine can be constrained: it never fabricates a number, never infers a comparison that wasn’t computed, and cites the filtering on every report. This is not a dashboard with a chat window bolted on. It is a single stack where the SQL, the prompts, and the output are all under the same roof — and all reviewable as code.
Pipeline
[Brand] · Monthly report
2026-03-01 → 2026-04-01
Key Insights · 3 + 1
- · 91% of quiz respondents don’t know their hemoglobin level.
- · HCP resource downloads up 34% month-over-month.
- · Patient-portal logins concentrate on Tuesday mornings.
- · 89% of raw events survived filtering — exceptionally clean traffic.
Unique visitors
2,104
+12%
Outcome rate
17.6%
+6.5pp
Pages / visitor
3.2
±0.0
Demonstration
This is what a real Silo report looks like, unedited.
One brand. One month. Three insights plus a data-quality line. Filtering transparent, terminology strict, compliance-ready. Shipped March 2026 for a live Canadian rare-disease patient program.
How we’re different
You’re already comparing us to these three. Here’s what the comparison actually looks like.
| Segment + GA4 | GenAI on a warehouse | Roll-your-own analyst | Silo | |
|---|---|---|---|---|
| Canadian data residency | No | Depends on warehouse | Yes, if you build it | Yes, by default |
| PII / bot filtering at the event layer | No | No | Manual | Server-side, by rule |
| Monthly outcome report per brand | No | Hallucinated | 2–3 weeks of a person | Shipped on day one |
| No-hallucination enforcement on AI output | N/A | No | Human judgement | Prompt-enforced |
| Multi-brand agency UX | Workspace fatigue | No | Per-brand setup | Built for it |
Every other path forward has one of two failure modes. Either the data is dirty and the AI invents insights on top of it, or the data is clean and a human is spending three weeks a month writing the report by hand. Silo is the only stack that owns the pipe and the prompts in one place — which is what makes “no hallucinations” a product guarantee instead of a promise.
The fastest way to evaluate Silo is to see it run against your own brand’s data.
Act 3 · Result
What you can now do
Three things every pharma digital team gets on day one.
Outcome 01
Ship a defensible monthly report per brand.
Your compliance team sees filtering counts, your stakeholders see the three insights that matter, and you stop paying $80k–$150k a year per brand for a human analyst to write something the brand will ignore by Q3.
Outcome 02
Run every brand site through one residency-controlled pipe.
One Segment-compatible SDK, one Canadian event plane, one debugger and DAG visualizer that actually answers “why didn’t this event fire in GA4” — instead of workspace-per-client fatigue and a Slack thread with Twilio support.
Outcome 03
Let AI analyze regulated data without worrying what it invents.
Because the SQL layer, the filtering, and the prompts are all governed in one stack, the Report Engine can be prevented from hallucinating by construction — not by disclaimer.
Why you can trust this
Not a pilot. Not a demo. A live production stack.
Silo runs the event pipeline and monthly reporting for eight live Canadian pharma and regulated-brand programs today. Between May 2025 and April 2026 it shipped 33 monthly reports — the longest-running brand on the stack has eleven consecutive months, with a second brand at eleven months through a documented methodology evolution across versions two, three, four, and five. The product isn’t a pitch for what we’ll build. It’s the stack The Adpharm uses on Monday morning to ship the reports its clients read with compliance and legal in the room.
See it against your own data, in 30 minutes.
A 30-minute walkthrough on a live pharma brand: the event pipeline, the filtering transparency, and an actual monthly report from the longest-running brand on the stack. Then we scope what instrumenting your site would look like — no slide deck, no follow-up sequence.