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Cachee for IoT & Messaging Platforms

21 Billion Devices. Billions of Messages.
Every State Read at 17ns.

Every SMS routed requires 6–12 state lookups: opt-out lists, carrier rules, throughput limits, campaign compliance, delivery status. Every IoT device command requires device state, firmware version, connectivity status, last heartbeat. At 1–10ms per Redis read, state lookups become the bottleneck at scale. Cachee serves them all from L1 at 17ns.

TwilioSinchInfobipVonageTelnyxBandwidth AWS IoTAzure IoTCisco IoTPTC ThingWorx
21.1B
IoT Connections
Dec 2025 estimate
$82B+
A2P SMS Market
2023, 5.5% CAGR
$865B
IoT Market 2030
$547B in 2025, 9.6% CAGR
17ns
State Read
vs 1–10ms Redis
Live Message Routing Simulation
Watch Every State Check in the Message Pipeline

An A2P message arrives. Before it reaches the carrier, the platform must check opt-out status, campaign compliance, carrier routing, throughput throttle, and more. Watch how state read speed affects total message latency.

📱 OTP To: +1 (305) ***-4821 From: 10DLC #48291 Campaign: AUTH-VERIFY Carrier: T-Mobile
🔴 Standard Pipeline (Redis)ms-class
Total routing time:
🟢 Cachee-Enhanced Pipeline (L1)ns-class
Total routing time:
0
Messages Routed
0ms
Standard Avg
0ms
Cachee Avg
Routing Speedup
0
Extra MPS Capacity
Two Billion-Scale State Problems. One Solution.
Messaging Platforms and IoT Systems Share the Same Bottleneck
📱 A2P SMS & Messaging
6–12 State Reads Per Message. Billions of Messages Per Day.
Before Twilio sends a single SMS, it must check: Is this number opted out? Is the campaign registered (10DLC)? What's the carrier? What's the current MPS throughput for this sender? Has the daily limit been hit? What's the best route (cost vs. reliability)? Each check hits Redis or Cassandra at 1–10ms. At 1M messages/minute, these state reads consume more compute than the actual message delivery.
$0.0083/msg × 10ms overhead = $48M/yr in wasted compute
🌐 IoT Device Management
21 Billion Devices. Real-Time State for Each One.
AWS IoT Core manages millions of device shadows — JSON documents representing device state (online/offline, firmware version, sensor readings, last heartbeat). Every command sent to a device requires reading its current state. Every telemetry event requires updating it. At cloud latency (5–50ms per read), real-time decisioning across millions of devices is impossible. Edge computing helps but fragments state.
1M devices × 10 reads/sec × 5ms = 50,000 CPU-seconds/sec
The State Read Tax
Your Infrastructure Is Fast. Your State Lookups Aren't.
🚫
Opt-Out Compliance at Scale
TCPA violations cost $500–$1,500 per message. Checking opt-out lists must be instant and never stale. At 10B+ messages/day across the industry, even Redis at 1ms per check means 10M compute-seconds per day just for opt-out verification. A single cache miss sending to an opted-out number: $1,500 fine.
$1,500/message TCPA fine
Throughput Throttle State
10DLC numbers have carrier-imposed MPS limits tied to trust scores. The platform must track real-time message counts per sender, per campaign, per second. Stale throttle state means either: over-sending (carrier blocks the number) or under-sending (wasted capacity). Both cost money.
Trust score drives MPS limits
🌐
IoT Device Twin Lag
Device twins (AWS IoT Shadows, Azure Digital Twins) store desired vs. reported state. When desired ≠ reported, the platform sends commands. But if the twin read takes 5–50ms, the platform is making decisions on stale state — sending commands to devices that have already changed. This causes command storms, duplicate actions, and wasted bandwidth.
5–50ms twin read latency
Architecture
Cachee Accelerates Both Messaging and IoT State
1
Opt-Out & Compliance Cache
Every phone number's opt-out status, DNC list membership, and TCPA consent state cached in L1. Updated in real-time as opt-outs arrive. Zero-latency compliance check on every message — no risk of stale data sending to opted-out numbers.
2
Carrier Route & Throttle State
Real-time MPS counters per sender, per campaign, per carrier maintained in L1. Route selection (cheapest vs. most reliable carrier path) resolved in nanoseconds. Throughput limits enforced without Redis round-trips — never over-send, never under-utilize.
3
Device State Acceleration
Hot device states (the 20% of devices generating 80% of events) cached in L1. AI predicts which devices will need state reads based on telemetry patterns. Device twin reads at 17ns enable true real-time control loops — not 50ms-delayed approximations.
4
Edge-Cloud State Sync
Cachee runs at both edge and cloud tiers. Edge nodes cache local device state for sub-millisecond reads. Cloud aggregates global state. Bi-directional sync ensures consistency without the latency penalty of cloud-only architectures.
Revenue Impact
The Math for a Twilio-Scale Platform
470× Faster
Message Routing State Lookups — Enabling 10× Higher MPS Per Server
10×
MPS per server
with Cachee
17ns
Opt-out check
vs 1–3ms Redis
-60%
Infrastructure cost
at same throughput
Zero
Stale opt-out risk
real-time compliance
For a messaging platform processing 1B messages/day: Each message requires ~8 state lookups averaging 3ms each = 24ms of state read time per message. On a single server doing 100 MPS, 2.4 seconds of every second is spent on state reads — meaning you need 3 servers just for the state overhead. With Cachee at 17ns per read, total state time drops to 136ns per message. The same server now handles 1,000+ MPS. That's a 60% reduction in routing infrastructure.
For IoT fleet operators managing 1M+ devices: Real-time device state at 17ns enables true closed-loop control. Instead of sending a command and waiting 50ms to verify state change, Cachee confirms device state in nanoseconds — enabling autonomous IoT operations where the platform reacts to sensor data and updates commands in the same millisecond. This is the "agentic AI" layer that IoT Analytics identifies as the next wave.
Benchmark Cachee on Your Messaging or IoT Infrastructure →
Drop-in Redis acceleration · Measure MPS improvement in 24 hours · Built by a team that's run texting platforms at scale
Cachee — L1 State Caching for Messaging & IoT Infrastructure · Patent pending · Market data via MarketsandMarkets, Mordor Intelligence, IoT Analytics