Context Platform for AI Applications

Persistent memory for AI agents.

Hardcarrx gives AI applications persistent memory, semantic cache, provider routing, and request-level observability through one control plane. Ship one endpoint, then scale with context.

OpenAI-compatible API
Per-workspace memory isolation
Built for AI agents
Provider-agnostic routing
Request-level observability

Live memory active

One endpoint, four operational layers

Healthy
Cache savings49.4%
Memory latency<100ms
User isolationOn
Routing request

Policy matched: low-latency model

SDK / CLI onboarding

hardcarrx chatbox --model gpt-4.1-mini \ --provider openai \ --api-key hxv_your_api_key
RoutingProvider selected by policy
CacheExact + semantic matching
MemoryStored context items by workspace
LogsRequest-level traceability

Features

Everything your AI product needs before launch.

Hardcarrx gives you the memory, cache, routing, and observability primitives needed to ship production AI experiences with less reinvention and more operational clarity.

01

Long-term memory

Store useful user preferences and retrieve them safely with per-user isolation and developer controls.

02

Semantic cache

Reduce repeated model calls by matching similar requests and serving trusted cached responses.

03

One gateway API

Route AI traffic through an OpenAI-compatible interface with observability, keys, limits, and billing hooks.

Developer onboarding

Ship with one endpoint, then layer in memory, cache, and observability

Start with the simplest production path first. Point your app at Hardcarrx, attach one Hardcarrx API Key, and progressively tune provider routing, retention policy, and request visibility from one control plane.

Quick start

pip install git+https://github.com/Hardcarrx/Hardcarrx-SDK.git hardcarrx chatbox --model gpt-4.1-mini \ --provider openai \ --api-key hxv_your_api_key
Provider abstraction without app rewrites
Stored context-item controls and policy limits
Request logs for cache, memory, and spend visibility

Memory + cache advantage

Turn every request into a better next response.

Cache improves cost and latency now. Memory improves product quality over time. Hardcarrx lets teams keep both layers in one governed platform so continuity compounds without locking your experience to a single provider.

Persistent user and workflow profiles

Maintain memory by user, team, and journey with explicit retention controls built for enterprise governance.

Relevance-first retrieval at inference time

Inject only high-value context into prompts to raise answer quality while containing token growth and latency.

Provider-independent continuity and quality

Keep user experience stable even when routing changes—memory remains your product IP, not a single model vendor dependency.

Call flow

See one request move through route, cache, and memory

HardCarrx combines routing, cache, and memory in a single operating layer for faster and more reliable AI responses.

Step 1

Client Request

Step 2

Smart Router

Step 3

Cache Layer

Step 4

Memory Layer

Step 5

Provider Response

Pricing

Plans built for memory-enabled AI workloads

Clear usage limits for memory-enabled AI workloads, with calm upgrade paths as routing, cache, and continuity become production-critical.

Free

Best for: POCs and internal validation

$0

  • 1,000 memory-enabled requests / month
  • 1 workspace
  • 10,000 context items
  • 14-day retention
Start free

Starter

Best for: Early production workloads

$9

/ month

  • 10,000 memory-enabled requests / month
  • 2 workspaces
  • 50,000 context items
  • 30-day retention
Get started

Pro

Most Popular

Best for: Revenue-critical AI experiences

$29

/ month

  • 50,000 memory-enabled requests / month
  • 5 workspaces
  • 300,000 context items
  • 180-day retention
Get started

Team

Best for: High-scale production and multi-team ops

$99

/ month

  • 250,000 memory-enabled requests / month
  • 10 workspaces
  • 2,000,000 context items
  • 1-year retention
Get started
  • Memory-enabled requests: Calls where HardCarrx stores and uses memory to personalize future responses.
  • Context items: Individual saved pieces of memory like preferences, facts, or conversation notes.

Ready to ship AI memory infrastructure without rebuilding the stack?

Create your account to configure one endpoint for routing, semantic cache, durable memory, and request-level observability.

Production controls in one gateway layer