// LIVE
99.97% uptime SLA guaranteed • <40ms average inference latency • SOC 2 Type II certified • 1M+ API calls processed daily • GDPR & HIPAA compliant • Y Combinator W26 applicant • 47% average reduction in client operational costs • ISO 27001 in progress • 3x faster model deployment than industry average • Zero-downtime deployment pipeline • 99.97% uptime SLA guaranteed • <40ms average inference latency • SOC 2 Type II certified • 1M+ API calls processed daily • GDPR & HIPAA compliant • Y Combinator W26 applicant • 47% average reduction in client operational costs • ISO 27001 in progress • 3x faster model deployment than industry average • Zero-downtime deployment pipeline •
Next-Generation AI Infrastructure

ClexerI
Technologies

Cognitive  Learning  Engine for e Xtended  Enterprise  Reasoning  Innovation

We build the infrastructure that makes artificial intelligence not just smarter, but operationally transformative — from the ground up, for enterprises that refuse to compromise.

Explore Our Platform Join the Team
$4.2M
Pre-Seed Raised
40ms
Inference Latency
99.97%
Uptime SLA
1M+
Daily API Calls
2 yrs
Proven Track Record

Applying to Y Combinator W26

ClexerI Technologies is actively pursuing the Winter 2026 batch of Y Combinator. We believe our proprietary Cognitive Learning Engine architecture represents a category-defining leap in enterprise AI deployability — and we're bringing that thesis to the world's most prestigious accelerator. Join us before the rocket ignites.

Application In Progress →
What We Are

The Acronym
Behind the Engine

Every letter in ClexerI stands for a core engineering principle — not a buzzword, but a verifiable design pillar baked into every system we ship.

C
Cognitive
Our models don't pattern-match — they reason. ClexerI's proprietary CORE (Contextual Object Reasoning Engine) architecture enables multi-hop inference across structured and unstructured data simultaneously, mimicking the associative cognition patterns of human experts with measurably higher throughput.
L
Learning
Continuous, federated, and privacy-preserving. Our adaptive learning loops let enterprise models improve on live production data without ever exposing raw records. Delta fine-tuning pipelines achieve 94.3% of full-fine-tune performance at 12% of the compute cost.
E
Engine
Not a wrapper. Not an API proxy. A full-stack inference engine — from quantized weight storage at the edge to distributed load-balanced GPU clusters in our sovereign cloud. We own every layer of the stack, which is why we can guarantee the SLAs nobody else will sign.
eX
eXtended
Designed for the long context world. Our transformer variants support up to 2M token context windows with sub-quadratic attention complexity via sparse-hybrid mechanisms. Entire codebases, legal corpora, and multi-year customer histories become first-class reasoning inputs.
E
Enterprise
Zero-trust by default. Role-based prompt segmentation, full audit logging, SAML 2.0 SSO, and private VPC deployment options. We pass infosec review with enterprise security teams — including Fortune 100 firms who benchmarked us against incumbents with 200-person security organizations.
R
Reasoning
Our ReasonChain™ framework decomposes complex multi-step decisions into verifiable logical trees. Every conclusion is traceable to the evidence chain that produced it — a requirement for regulated industries where "the AI said so" is not a sufficient audit trail.
I
Innovation — the non-negotiable
The I in ClexerI is the load-bearing letter. It's the reason we're not building incremental improvements to existing AI tooling — we're engineering the architecture that the next decade of enterprise intelligence will run on. Innovation isn't a department at ClexerI. It's the operating system.
Verified Performance

Numbers That
Don't Apologize

99.97%
Uptime SLA — contractually guaranteed across all production tiers
<40ms
P99 inference latency at 1K token output on standard enterprise workloads
1M+
API calls processed daily across all active client deployments
47%
Average reduction in operational costs reported by enterprise clients within 6 months
3x
Faster model deployment cycle versus industry-standard MLOps toolchains
2M
Token context window — the largest commercially available in our price tier
94.3%
Fine-tune parity using our delta-learning approach at 12% of full training compute
$4.2M
Pre-seed capital raised from top-tier angel investors and institutional funds
Zero
Production data breaches in 2 years of operation — not one incident
SOC 2
Type II certified — audited controls across Security, Availability, and Confidentiality
12
Enterprise clients onboarded in the past 18 months across 4 industry verticals
24/7
Dedicated engineering support with <15-minute incident response SLA on P0 issues
Product Suite

Intelligent Systems
for Every Layer

Four interlocking products. One coherent stack. Deployed together or independently.

Core Inference
APEX Engine
ClexerI's flagship inference runtime — a production-hardened serving layer for large language models that achieves sub-40ms P99 latency through speculative decoding, KV-cache tiering, and continuous batching at scale.
  • Speculative decoding with draft-model acceleration
  • Multi-tenant KV-cache isolation with zero cross-leak
  • Horizontal auto-scaling tied to token throughput metrics
  • Supports GGUF, GPTQ, AWQ, and FP8 quantization formats
  • OpenAI-compatible API — drop-in replacement, zero code changes
Orchestration
NEXUS Workflow
A declarative agentic orchestration framework for building complex, multi-model workflows with deterministic control flow, human-in-the-loop checkpoints, and full auditability on every decision node.
  • DAG-based workflow definition with runtime introspection
  • Built-in rollback and retry logic with configurable backoff
  • Parallel agent spawning with result consensus strategies
  • Native integrations: Slack, Salesforce, SAP, ServiceNow, Jira
  • NEXUS Trace™ — full execution replay for compliance review
Fine-Tuning
DELTA Adapt
ClexerI's proprietary federated fine-tuning platform. Customize any foundation model on your private data without moving a single byte off-premises. Achieve expert-level domain accuracy with as few as 800 labeled examples.
  • Federated LoRA and QLoRA with differential privacy guarantees
  • Automatic hyperparameter search with Bayesian optimization
  • A/B deployment with live performance divergence tracking
  • Supports 7B–70B parameter base models on commodity hardware
  • DELTA Eval™ — automated red-teaming before any deployment
Observability
PRISM Analytics
Full-spectrum AI observability — from token-level cost attribution to hallucination rate tracking to RLHF feedback loops. The only platform that turns your AI deployment data into a continuous improvement engine.
  • Real-time hallucination detection via semantic consistency scoring
  • Per-request cost attribution down to individual business units
  • Drift detection with automatic retraining trigger thresholds
  • GDPR-compliant data retention with configurable PII scrubbing
  • Native SIEM integration — ships to Splunk, Datadog, Elastic
01

ReasonChain™ Framework

Every inference output can be decomposed into a verifiable logical tree, with each node traceable to the source token span that produced it. Mandatory for regulated industries. Unique to ClexerI.

02

Sovereign Cloud Deployment

Deploy entirely within your own VPC. ClexerI operates a zero-egress architecture option where no data ever touches our infrastructure — full model weights, inference, and logging remain in your perimeter.

03

Sparse Hybrid Attention

Our 2M-token context window is powered by sub-quadratic attention complexity — not a marketing claim with asterisks. Benchmarked at 2.3× cheaper per token than naive full-attention at equivalent context lengths.

04

Zero-Downtime Deployment Pipeline

Blue-green model swaps with automated canary promotion. Shadow inference testing before any production switch. Average deployment time: 8 minutes from commit to live. No maintenance windows. Ever.

05

GDPR, HIPAA & SOC 2 Type II

Compliance isn't an add-on here. Every system component was architected with regulatory requirements as first-class constraints — not retrofitted. We pass legal review in healthcare, finance, and federal government contexts.

06

Multi-Modal Backbone

Text, structured data, images, audio transcripts, and code — all as unified first-class input types. A single NEXUS workflow can reason across a recorded call, its CRM record, and three attachments simultaneously.

01
Owned Infrastructure
We run our own GPU clusters in carrier-neutral colocations across three regions. No hyperscaler markup. No shared-tenant noise floor. Your latency budget is yours, not a dice roll on someone else's queue.
02
Defense-First Security
Every API call is signed, every session is ephemeral, and every model interaction is logged to an immutable audit trail. We don't offer security as a feature tier — it is the foundation on which every tier is built.
03
Customer Obsession Measured in SLAs
We put contractual teeth on our claims. If uptime drops below 99.97%, we credit your invoice — automatically. We back every performance benchmark with a refund clause because we're confident in the engineering behind them.
Leadership

The People
Driving the Engine

// Founder & Chief Executive Officer
LE
Larry "Lucas" Errett
Founder & CEO — ClexerI Technologies

Larry "Lucas" Errett founded ClexerI Technologies two years ago with a single conviction: that the enterprise AI market would eventually demand infrastructure it could actually trust — and that nobody was building it correctly. Starting from a sparse-attention research prototype and a whiteboard full of architecture diagrams, Lucas bootstrapped the company's first product to paying customers within seven months, raising a pre-seed round shortly after.

In two years, Lucas has taken ClexerI from zero to a multi-product AI infrastructure platform processing over a million API calls per day, serving enterprise clients in financial services, healthcare technology, and logistics — and achieving SOC 2 Type II certification without external compliance consultants. He has personally designed core components of the APEX inference engine, authored the ReasonChain™ patent applications, and built the engineering team that now ships across four product lines simultaneously.

Lucas operates on the belief that enterprise AI's biggest unsolved problem isn't capability — it's operational trust. Every product decision at ClexerI flows from that principle. He is currently leading the company's Y Combinator application for the Winter 2026 batch.

2 Yrs Founding Experience Sparse Attention Architecture ReasonChain™ Patent Author Pre-Seed to SOC 2 in 24 Months YC W26 Applicant MLOps / GPU Infrastructure Federated Learning
Executive Statement — Larry "Lucas" Errett, CEO
lucas@clexeri:~$ ./statement.sh
Initializing executive context...
 
"Two years ago I started ClexerI because I was tired of watching enterprises buy AI products that were one abstraction layer away from being brittle. They weren't buying intelligence — they were buying the appearance of it. We built the actual thing. Every benchmark we publish is reproducible. Every SLA we sign is paid out of our own pocket if we miss it. We're applying to Y Combinator not because we need the stamp of approval — we need the network to scale what we've already proven works."
 
— Larry "Lucas" Errett, Founder & CEO, ClexerI Technologies
Recruiting

Build What Doesn't
Exist Yet

We're a small team that ships fast and cares deeply about correctness. If you want your work to matter at every layer of the stack, you're in the right place.

Senior ML Infrastructure Engineer

Full-Time · Remote (US/EU) · $180K–$240K + equity

Hot

Research Engineer — Sparse Attention

Full-Time · Remote-First · $160K–$210K + equity

Research

Enterprise Solutions Engineer

Full-Time · Hybrid (NYC / SF) · $130K–$170K + equity

Open

Platform Security Engineer

Full-Time · Remote (US) · $170K–$220K + equity

Priority

Head of Product — Enterprise AI

Full-Time · Hybrid (SF preferred) · $160K–$200K + equity

Leadership

DevRel / Developer Advocate

Full-Time · Remote · $120K–$155K + equity

Open
Recruiting Bulletin Board LIVE
DY
Derek Yan
2h ago
// Inquiring: ML Infrastructure Engineer
Hi ClexerI team — I've been following your architecture work for a while, especially the ReasonChain™ work and your approach to federated fine-tuning. I have 4 years in distributed ML systems (Kubernetes-native, CUDA-level optimization) and I'm genuinely excited about what you're building. Would love to have a conversation about the senior ML infra role. Happy to share a resume or jump on a call whenever works.
Under Review by Engineering Team
// Post a message to the board
Y Combinator Application

Why We're Applying
to YC W26

ClexerI Technologies has spent two years proving the core thesis: enterprise AI deployments fail not because the models aren't good enough, but because the infrastructure around them is fragile, opaque, and compliance-hostile. We've solved that problem. APEX, NEXUS, DELTA, and PRISM form a complete, production-hardened AI operating environment — and our early enterprise clients are showing us exactly how much room there is to run.

We're applying to YC Winter 2026 because scaling this company from 12 enterprise clients to 1,200 requires more than great engineering — it requires the network, the market credibility, and the compressed growth timeline that only YC's program delivers. We're not applying for validation. We have the product, the metrics, and the mission. We're applying for velocity.

If you're an investor, enterprise buyer, or potential co-applicant reference who has worked with ClexerI, Larry Errett is personally coordinating reference conversations ahead of the submission deadline.

Contact Lucas Directly Join Before Demo Day