The production problem
The problem isn't the AI. It's how it's built.
There’s a reason AI looks great in demos and falls apart with real customers. Most of it runs on one giant set of instructions trying to handle every scenario at once. On a simple chat, it works. When a real customer interrupts, changes their mind, goes off-topic, or pushes back — it cracks.
It forgets the field it was collecting. Asks questions that don’t apply. Collects all the data, then fails to actually submit it. Rewriting the prompt won’t fix it. The fix is in how the system is built.
The stress test
We stress-tested this. Here's what happened.
400 simulated conversations. 200 through MagicBlocks. 200 through a typical one- prompt system. Deliberately difficult customers — interrupting, wandering off-topic, contradicting themselves, pivoting mid-chat. The kind of customer your team deals with every day.
Send 1,000 leads through a one-prompt system: about 410 don't finish. Send 1,000
through MagicBlocks: about 25 don't finish. Same budget. Same traffic. Very different
outcome.
Z-score = 9.33 (p < 0.00001). This is the build — not luck.
Secondary metrics
Three more numbers the stress test surfaced.
Beyond task completion — three orthogonal measures of how the systems performed when conversations got hard.
One-prompt systems often collect all the data and don’t realise the job is done. MagicBlocks knows the checklist. It only says "complete" when it actually is.
The other system asked at least one off-topic question in every single run. MagicBlocks brought that down to 55% — and even those were soft edge cases. We only allow valid questions at each stage.
When a customer went off the rails, MagicBlocks pulled the conversation back 19% faster. Acknowledges the distraction, returns to the next step.
Guardian · the compliance layer
A separate AI reviews the reply. Before it leaves the system.
Speed and persistence only matter if the messages are controlled. Guardian is a separate AI that reviews replies before they reach a lead — your rules, your brand voice, factual accuracy, conversation quality. Replies that fail a check are rewritten automatically or queued for review.
Guardian sits on top of a Guardrails layer you configure — your team controls exactly how the AI behaves. No human has to remember the rules. The system enforces them.
-
Rules Engine
Set the exact rules your business runs by. Compliance requirements, brand boundaries, conversation rules, response standards. Applied to outbound messages — brand voice, compliance guardrails, factual grounding.
-
Rules Monitor
Even good rules can slip when conversations get complex. The Rules Monitor catches replies that break a rule and rewrites them — before they send. No human needed in the loop.
-
Jailbreak Prevention
In high-volume lead environments, bad actors show up. This blocks attempts to trick the AI into ignoring your rules or going off-script — no matter how the request is phrased.
-
Moderation
Catches anything harmful, offensive, or off-policy before it reaches a lead. Configurable to your standards.
-
PII Collection Control
You decide exactly what data the AI is (and isn’t) allowed to collect. Email, phone, financial data — you control what gets gathered and how.
-
Redaction
Turn on redaction and the data types you choose are stripped from conversation logs. You decide what counts as sensitive — it’s a setting, not a default.
-
Automatic FAQ Grounding
Product and service answers come from your verified knowledge base — not from the AI’s memory or guessing. The answer is from your data, not made up.
Built for regulated industries
The industries we work in don't forgive mistakes.
Mortgage. Insurance. Healthcare. Finance. Banking. These aren’t casual industries where a rough AI interaction gets laughed off. A non-compliant message, a mishandled data request, or a poorly handled privacy objection creates real problems for your customers and your business. MagicBlocks was built for this — not retrofitted.
-
SOC 2 Type II Certified
Annual third-party audit of security controls, availability, and data handling. Not a self-assessment — independent verification.
-
ISO 27001 Certified
The international standard for information security. Systematic, documented, and audited.
-
TCPA-aligned
Consent management, opt-out handling, do-not-contact enforcement — built into the messaging layer, not bolted on.
-
Your data, in your region
Data stays where your regulations require. Dedicated storage in the US, Europe, and Australia. No workarounds.
-
Fast global response
Replies in milliseconds across our global edge network. Built to minimise regional latency.
-
End-to-end encryption
Data encrypted in transit and at rest. Your conversations are not used to train shared models.
-
99.9% uptime target
Designed to minimise maintenance-window interruptions. Automatic failover across regions and model providers.
Running in production
This isn't a pilot. It's running every day.
MagicBlocks is live across some of the most demanding lead environments in the market — industries where reliability isn’t a selling point, it’s a prerequisite.
We work with Beeline — NASDAQ-listed, high-volume, high-stakes mortgage lending — running real lead conversations at scale, day and night. Alongside operators across mortgage, finance, auto, home services, healthcare, tourism, legal, SaaS, and creative. These aren't pilots. They're running the same way you would run it.
The bar for AI in regulated financial services isn’t "it works in demos." It’s "it holds up when a real customer pushes back, the compliance team audits the logs, and the CTO asks hard questions about how it’s built." That’s the bar we built to.
The architecture
Not a bigger prompt. A better system.
The difference comes down to one decision in how it’s built: specialised parts, or one giant prompt. Most AI sales tools take everything in at once, try to remember it all, and start to slip when pressure hits.
MagicBlocks runs specialised playbooks — opening, qualifying, handling objections, following up, handing off — each small, focused, and rule-bound. The system keeps track of the whole thing. At every step, it tracks where the conversation is, what’s been collected, what’s still needed, and what comes next. When a customer interrupts or pivots, we pull the conversation back — because we know exactly where "back" is.
No workflow canvases. No visual builders that constrain how conversations flow. Just clean structure that gives the conversation room to feel human while keeping the process intact.
- Specialised each stage of the conversation has its own playbook
- Tracks where it is the system tracks the whole conversation, end to end
- Rule-bound each stage only allows actions valid for that stage
- Adaptive follow-up adjusts path, timing, and channel based on what the lead does
- Grounded answers come from your verified data, not from the AI guessing
From the engineering team
AI that holds up isn't fast first. It's controlled first, and fast after. Every customer we've won from a competitor has the same story — the demo was great, the real run wasn't, and nothing breaks trust faster than an AI that says something it shouldn't. So we built Guardian before we built speed, and we won't ship a change that weakens either one.
Sean co-built Bob, the mortgage industry’s first AI agent, at Beeline.
FAQ · Security review
Questions the security review asks.
Where is our data stored?
In the region you choose — US, Europe, or Australia. Data stays in your region. No cross-region replication unless you explicitly opt in.
Do you use our conversations to train your models?
No. Your data is used to improve your AI on your data — nothing crosses customer boundaries, nothing feeds model training. The underlying model providers we route to are configured to suppress training on your conversations as well.
How do you handle consent and opt-outs?
Opt-outs are honored on every message and propagate across every channel and campaign by design — as quickly as the system allows. Whenever a lead opts out, MagicBlocks stops messaging them everywhere. If a lead’s consent has expired under your rules, we won’t message them — consent is checked before each send.
What's your incident response process?
Defined, documented, and part of our SOC 2 audit scope. If there’s a security incident, customers are notified per the contractual SLA with root-cause analysis and remediation steps.
Can we audit conversations?
Yes. Every message is logged with timestamp, channel, content, outcome, and the rules it ran under. Role-based access lets your compliance team review anything later. Exports are audit-ready.
What's your uptime?
99.9% uptime target. Automatic failover across regions and model providers for the critical conversation path.
How do you handle PII?
You decide exactly what data the AI is allowed to collect. Optional log redaction can strip the data types you choose from conversation logs — it’s a setting you turn on, not a default. Encryption in transit and at rest. Role-based access for anyone viewing logs.
See it hold up.
Most demos show you the easy version. We'll show you what happens when the conversation gets complicated — and why how it's built is the difference.