IT Directors & Managers
Right now, an interface
in your network is failing silently.
You manage 200+ interfaces across multiple facilities. Your team is two analysts short. Last month, you found out about a lab result delivery failure from an angry physician — not from your monitoring dashboard.
Your APM shows green. Your Mirth console shows messages flowing. But somewhere between the ORU leaving the lab system and arriving at the EHR, three STAT troponin results are sitting in a queue that nobody is watching.
The gap in your monitoring
Your infrastructure dashboard says everything is green. HTTP 200 OK across the board.
Zero ORU messages with three STAT orders pending.
The pharmacy has not received a new medication order in 45 minutes.
An ADT discharge triggered but the downstream billing system never got the DRG update.
Your infrastructure monitoring confirms that systems are running.
It does not confirm that patients are being served. The gap between “the system responded” and “the message was clinically correct” is where silent failures live. That gap is where Loft operates.
You are responsible for infrastructure that delivers clinical data to clinicians making real-time decisions about patient care. And your visibility into that infrastructure is a Mirth dashboard that tells you messages moved, not that messages were correct.
What your current tools cannot see
Infrastructure monitoring and clinical message validation are two different problems. Only one of them is solved.
Silent structural failures
A vendor pushes an update that shifts a field format. Messages keep flowing. Downstream systems start rejecting them silently. Your dashboard stays green. The pharmacy stops receiving orders.
Volume anomalies nobody catches
Your lab interface usually sends 200 messages per hour. For the past 45 minutes it has sent zero. No error. No alert. Three STAT orders are sitting in a queue. You will find out when a physician calls.
Friday at 4:47 PM discoveries
Vendor updates hit production on Friday afternoons. Your on-call analyst finds the failure Monday morning, after a weekend of missed medication orders and delayed lab results.
What Loft shows you
Message-level observability. Not infrastructure monitoring. Loft validates every message as it flows through your interfaces — structural checks, volume thresholds, vendor profile conformance — and alerts within 60 seconds of a failure.
Up to 10 interfaces
- Real-time message-level validation
- Alerts within 60 seconds of a structural failure
- Volume anomaly detection — "Lab interface has sent zero in 45 minutes"
- Email, Slack, Teams notifications
Up to 50 interfaces
- Everything in Watch
- AI-guided remediation on every deviation
- Deviation classification: field format change, segment reorder, new Z-segment
- Severity assessment with fix guidance
- Trend dashboards and historical analytics
Unlimited interfaces
- Everything in Insight
- Self-healing: generates micro-ETL rules automatically
- Transforms and delivers queued messages without engineer intervention
- 1-click approval or autonomous mode per interface
- Alert your team in the morning, not at 2am
The director who knows before anyone calls
Monday morning, 7:14 AM. You open your laptop. The dashboard already shows what changed overnight, what Loft caught, and what your team resolved before rounds.
No surprises from physicians. No emergency Jira tickets. The CMO asks how your interfaces are performing and you show her real data — not a spreadsheet you updated last Tuesday.
Lab Interface — HL7 ORU
1,847 messages
Pharmacy — RXE Orders
Format deviation caught
ADT Admissions
203 messages
Radiology — DICOM Worklist
89 messages
Billing — DRG Updates
412 messages
No physician escalations overnight. 1 deviation caught and resolved autonomously.
Friday, 4:47 PM — Vendor Update Detected
RXE.2 field format shifted from NDC-10 to NDC-11
A vendor pushes an update that shifts the RXE.2 field from NDC-10 to NDC-11 format. Your pharmacy interface starts rejecting every new medication order. Loft catches it in 38 seconds.
With Loft Watch
Your on-call analyst gets a Slack notification and is working the issue by 4:48 PM. The failure window is minutes, not the weekend.
With Loft Command
The system generates a format normalization rule, delivers the queued orders, and your analyst reviews Monday morning. Zero patients affected.
When Loft detects a structural interface failure, you receive an alert within 60 seconds. If a structural failure reaches a downstream system without triggering a Loft alert, your next month is free.
Built for the director accountable to the CMO
Every feature maps to a real leadership concern: visibility, risk, uptime, and the quarterly review.
60-second structural alerts
When a message fails structural validation — wrong field format, missing required segment, unknown Z-segment — your team is notified within 60 seconds. Not the next morning.
Volume anomaly detection
Loft learns baseline throughput per interface. When a channel goes quiet — zero messages for 20 minutes when the baseline is 200 per hour — you get an alert before anyone downstream notices.
AI-guided remediation
When Insight detects a deviation, it tells your analyst what changed, why it likely happened, and how to fix it. Not just 'validation failed.' The full context your team needs to resolve it in minutes.
Self-healing pipeline
Command generates a micro-ETL rule, transforms queued messages, and delivers them — autonomously, or with 1-click approval. The pharmacy stays running. Your engineer reviews in the morning.
Historical analytics and trend dashboards
90-day retention. Per-channel throughput, error rate trends, and failure pattern analysis. The data you need for the quarterly review — without building it from Splunk queries.
Multi-interface correlation
Trace a patient's messages across interfaces. ADT from registration, ORU from the lab, RXE from pharmacy. When something goes wrong, you can trace it — not just alert on it.
The cost of the monitoring gap
Every silent failure has a cost. Loft pays for itself when it catches one Friday afternoon pharmacy outage before your weekend on-call does.
Mean time to detection
Before Loft
2–8 hours (physician call)
With Loft
60 seconds
Mean time to resolution
Before Loft
4+ hours
With Loft
Minutes (Insight) / Autonomous (Command)
Weekend on-call escalations
Before Loft
Every vendor update cycle
With Loft
Resolved before Monday
CMO reporting
Before Loft
Spreadsheet updated last Tuesday
With Loft
Real-time dashboard
Annual reactive support cost estimate
$240,000 / year
in reactive support costs. Preventable.
Loft Command at $50K/yr
Eliminates the majority of reactive MTTR cycles for structural failures. ROI positive within the first quarter for any organization with 50+ active interfaces.
What you bring to the next board meeting
Where to start
Each product in the Pidgeon platform serves a different operational need. Loft is built for the director accountable for uptime.
Standardize testing before deployment
Free CLI. Your analysts use the same validation rules, the same vendor profiles, the same reporting format across every project. Catch failures in dev and UAT — before they reach production.
Learn about Post →Realistic test environments for UAT
Generate entire synthetic patient populations for database seeding. No PHI. No compliance risk. Epidemiologically grounded so your UAT environment actually resembles production load.
Learn about Flock →Real-time production monitoring
Message-level validation, 60-second alerts, AI-guided remediation, and self-healing. The monitoring layer that fills the gap between “system running” and “patients served.”
Join Waitlist →Join Loft Founding Members
We are onboarding a small number of healthcare organizations for early access. Priority deployment. Direct line to the engineering team.
Founding members set the product roadmap. When your team needs a feature — a new alert channel, a vendor profile, a compliance export — it moves to the top of the queue.
The next silent failure is already in your network.
Join the Loft waitlist. Priority access for founding healthcare organizations. Direct line to the engineering team.