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Empirical head-to-head benchmark results

Context Without Limits.
Memory Without Loss.

Drop-in OpenAI-compatible API with persistent lattice memory. Crystallize documents once into permanent Lattice Nodes and recall Grounded Facts through a compact scoped viewport. Official-scale results: 96.28% exact (466/484) on RULER MRCR v2 and 54.87% (276/503) on LongBench v2.

92.8%
Token Cost Cut
Eliminates 2,090,000+ redundant prompt tokens on upstream LLMs in paired evaluations.
4.53×
Faster Response Time
1,375 ms Time-to-First-Token vs 6,227 ms on 850k+ token code repositories.
100%
Zero-Collision Precision
Perfect resolution across 42 enterprise redline amendments (vs 7.1% baseline confusion).
$0.02
Multi-Turn Session Cost
Fixed $0.02 per 10-turn interaction vs $12.50–$25.00 on traditional monolithic prefill.
Empirical Head-to-Head Evaluation

Head-to-Head: LLM Alone vs. LLM with Calera ICX

Paired evaluation used Google Gemini 3.5 Flash-Lite (gemini-3.5-flash-lite) as the upstream BYOK test model. ICX works with any supported LLM — Gemini was the model we ran for this comparison. Same tasks, same weights — ICX separates permanent lattice storage from the generative viewport so the model receives only the facts it needs.

Upstream test model Google Gemini 3.5 Flash-Lite · API ID gemini-3.5-flash-lite · BYOK via Google AI API
LLM alone Gemini 3.5 Flash-Lite · full context prefill
LLM + Calera ICX Gemini 3.5 Flash-Lite · scoped viewport

Long-context reasoning

LongBench v2 paired control · n=10 · identical sample IDs

Gemini 3.5 Flash-Lite alone
6/10 (60.0%)
2,253,544 prompt tokens
Gemini 3.5 Flash-Lite + ICX
6/10 (60.0%)
162,923 prompt tokens
Same quality · 92.77% fewer tokens · 13.8× efficiency

Needle retrieval

RULER MRCR · 484 rows · multi-round ordinal disambiguation

Gemini 3.5 Flash-Lite alone
Attention diffusion
Severe needle loss on deep haystacks · $12.50+ / session
Gemini 3.5 Flash-Lite + ICX
96.28% (466/484 exact)
Wilson 95% CI: 94.2%–97.6% · $0.02 / session
466/484 exact matches · 625× cost compression

Contract redlines

Enterprise disambiguation · 42 queries · MSAs, EHR, support tickets

Gemini 3.5 Flash-Lite alone
7.14% (3/42)
Full-prompt baseline · semantic collision on amendments
Gemini 3.5 Flash-Lite + ICX
100% (42/42)
Two-stage scoped viewport · zero collision
+92.86 pp improvement · 72.43% token cut

Code repository comprehension

852k context · deep AST & cross-file · sample 66fa208b

Gemini 3.5 Flash-Lite alone
6,227 ms (hit)
852,861 full prompt tokens
Gemini 3.5 Flash-Lite + ICX
1,375 ms (hit)
31,783 tokens · 4.53× faster
4.53× latency acceleration · 88.81% token cut
View full scorecard table
Benchmark & workload Gemini 3.5 Flash-Lite alone Gemini 3.5 Flash-Lite + ICX Advantage
LongBench v2 paired
n=10 matched sample IDs
6/10 · 2,253,544 tokens 6/10 · 162,923 tokens 92.77% token cut · quality parity
RULER MRCR
484 rows
Attention diffusion · $12.50+/session 96.28% (466/484) · $0.02/session 625× cost compression
Enterprise redlines
42 queries
7.14% (3/42) 100% (42/42) +92.86 pp · 72.43% token cut
Code repository
852k context
6,227 ms · 852,861 tokens 1,375 ms · 31,783 tokens 4.53× faster · 88.81% token cut
Legal & Compliance
Contract Redlines & MSAs
Track indemnity, liability, and amendment clauses across dozens of contract revisions without ordinal confusion between versions.
Software Engineering
Massive Code Repositories
Traverse AST dependency graphs and cross-file references across monorepos that exceed standard context windows.
Customer Support & CRM
Multi-Turn Ticket Vaults
Keep years of customer dialogue in persistent memory instead of re-uploading full ticket history on every agent turn.
Deep Document Search
Needle-in-a-Haystack Recall
Retrieve exact facts from deep document haystacks without lost-in-the-middle attention degradation.
Architectural Foundation

The Desk-and-Warehouse Principle

Why re-sending 1,000,000 tokens on every prompt turn burns tens of thousands of dollars — and how Calera ICX changes the physics of enterprise memory.

Without ICX
Standard 1M+ monolithic LLM context window
  • Token waste: Re-sends the full corpus on every single turn, multiplying upstream LLM costs.
  • Quadratic latency: Long prefill delays before the model can emit the first token.
  • Lost-in-the-middle: Attention diffuses across haystacks, causing semantic collisions and missed facts.
High TCO • Slow TTFT • Context diffusion
Enterprise Grade

Features Built for Enterprise Scale

Everything your engineering, security, and product teams need to deploy infinite context memory with zero compliance or performance friction.

Zero-Trust BYOK Security

Bring Your Own Google Gemini or OpenAI API keys. Keys are forwarded ephemerally via request headers (X-LLM-API-Key) with zero server-side key retention or training on customer data.

Drop-In OpenAI SDK Gateway

100% compatible drop-in replacement for standard OpenAI SDKs in Python, Node.js, Go, and Rust. Simply update baseURL and pass X-Space-ID to begin grounding requests.

Hosted Agent MCP Server

Native 1-click Model Context Protocol (MCP) server integration for Google Antigravity, Claude Desktop, Cursor, and custom autonomous agent swarms.

Explore Hosted MCP Docs →

Isolated Memory Workspaces

Multi-tenant namespace isolation (legal_vault, eng_repo, clinical_ehr) ensures zero cross-tenant factual leakage and instantaneous context switching.

Sub-Millisecond Engine Latency

Discrete simplicial graph diffusion executes on standard CPU memory in <0.5ms, eliminating expensive GPU cluster reservation fees and VRAM memory starvation.

Topological Grounding Invariant

Factual assertions form closed simplicial chains (∂c = 0). Hallucinated or out-of-ontology statements trip the boundary refusal operator instantly.

1-Line Integration

Developer SDK Quickstart

Drop Calera ICX into your existing OpenAI, LangChain, LlamaIndex, or REST workflows in less than 60 seconds.

baseURL: "https://icx.api.caleralabs.com/v1"
import requests
from openai import OpenAI

API_KEY = "icx_live_your_api_key"
BASE_URL = "https://icx.api.caleralabs.com/v1"
SPACE_ID = "legal_vault"

# 1. Ingest document into isolated memory space via REST API
with open("contracts/vendor_agreement.pdf", "rb") as f:
    requests.post(
        f"{BASE_URL}/ingest/file",
        headers={"Authorization": f"Bearer {API_KEY}", "X-Space-ID": SPACE_ID},
        files={"file": f}
    )

# 2. Query associative memory via standard OpenAI client drop-in
client = OpenAI(
    api_key=API_KEY,
    base_url=BASE_URL,
    default_headers={"X-Space-ID": SPACE_ID}
)

response = client.chat.completions.create(
    model="calera-icx-v1",
    messages=[
        {"role": "user", "content": "Recall exact contractual indemnity cap across all MSAs."}
    ]
)

print(response.choices[0].message.content)
Get API Key →
TCO Calculator

Enterprise Memory ROI & Scale Calculator

Estimate API cost savings and latency reduction when moving team-wide and enterprise document archives into ICX persistent lattice memory.

Real-World Scale Presets:
Real-World Benchmark Representation

SaaS Engineering Team (Team Tier — 5,000,000 Lattice Nodes): Equivalent to 100s of product specs, 50 enterprise MSAs, full API documentation, and 6 months of customer support logs (~10,000 source pages / ~1,250,000 Grounded Facts) crystallized in persistent memory.

Standard LLM Token Re-ingestion (Prefill)
$375,000 / mo
Exceeds single LLM prompt limit • Requires constant re-uploading
Calera ICX Continuous Lattice + BYOK
$187 / mo
< 0.5s response • Includes $149/mo Team Subscription + BYOK LLM Tokens
Save 99.9% ($374,813/mo)
Scientific Research Whitepaper

Looking for Raw Mathematical Proofs & Simplicial Geometry?

Read our full scientific report: "Infinite Memory Is Not Infinite Attention" for formal nilpotent boundary proofs (∂² = 0), discrete Hodge de Rham diffusion derivations, and SHA-256 reproducibility manifests across LongBench v2 and RULER MRCR suites.

Read Scientific Research Paper
4D A₄ simplicial manifold topology
Discrete Hodge Laplacian (Δγ = 0)
Thermodynamic activation barriers (ΔE)
Exhaustive 18-Miss RULER Taxonomy
SHA-256 Public Test Manifests

Subscription Tiers

Select a developer preview tier. All subscriptions include single-account management and multi-domain billing on Calera Labs.

💡 How ICX Persistent Memory Capacity Works

Your subscription tier grants persistent memory capacity (Lattice Nodes) in the Volumetric Lattice Network. Documents stay crystallized in your tenant lattice. On each prompt, ICX projects a numbered viewport of Grounded Facts into your LLM. Token savings depend on the workload (LongBench v2 mean noise cut on 503 rows is 51.98%; synthetic haystack gates are higher).

Monthly Billing Annual Billing Save 20%
Developer Preview

Developer Pilot

For individual developers testing persistent memory workflows.

$0/mo
  • 1,000,000 persistent Lattice Nodes (~2,000 source pages)
  • 1 Active API Key limit
  • 1 Isolated Memory Workspace
  • Projects ~500–1,000 Grounded Facts per turn
  • 30 requests/minute burst
  • OpenAI SDK Drop-In
Start Free Pilot
Developer Preview

Team

For engineering teams building memory-augmented AI applications.

$149/mo
  • 500,000,000 persistent Lattice Nodes
  • 10 Active API Keys
  • Shared team memory spaces
  • Multi-tenant namespaces
  • 150 requests/minute burst
  • Email + Slack support
Upgrade to Team
Production

Scale

For production AI workloads and heavy context applications.

$999/mo
  • 5B Lattice Nodes / mo engine allotment
  • Unlimited applications
  • Multi-tenant isolation
  • ~2M API calls / day
  • 99.95% uptime SLA
  • Priority support
Upgrade to Scale
Dedicated Cluster

Enterprise

Self-hosted + unlimited + white-glove. Contact sales.

Custom
  • Unlimited Lattice Nodes & calls
  • Self-hosted license
  • Hardware attestation
  • Dedicated engineering
  • SSO / custom SLA
  • Contact sales — no self-serve Checkout
Contact Sales
Dedicated Infrastructure

Dedicated Enterprise Worker Nodes

Provision isolated, high-throughput Cloud Run worker instances with guaranteed 1,500 req/min burst rates, dedicated CPU/memory specs, and private memory space isolation for enterprise security requirements.

Contact Sales & Engineering View Enterprise Architecture Docs