Verified Enterprise Proof

Documented Engineering Outcomes, Not Hypothetical AI Claims

Explore how SUDO's 12-person senior technical consulting team solves complex architectural challenges. Every deployment is benchmarked against strict latency, precision, and efficiency metrics.

LLM Systems & RAGSector: Global Financial Infrastructure
Production Active

Multi-Index Hybrid Retrieval for 40M+ SEC Filings

Replaced an unmaintainable legacy keyword engine with a deterministic hybrid vector-sparse retrieval topology, maintaining sub-second query latency and zero hallucinated citations.

Verified Technical Stack
Llama-IndexQdrant ClusterFastAPITensorRT-LLMAWS Bedrock
Retrieval Precision
99.4%
+38% vs baseline
P95 Query Latency
210ms
-74% reduction
Context Window Efficiency
4.2x
token cost halved
Engineering Challenge:

High document density with strict compliance constraints caused frequent context window overflows and citation drift across unstructured quarterly reporting datasets.

Architectural Intervention:

SUDO engineered a dual-stage reranking pipeline using customized cross-encoders, dynamic metadata partitioning, and isolated self-hosted vector indexing on dedicated infrastructure.

LLM Systems & RAGSector: Enterprise Legal Operations
Production Active

Domain-Tuned Clause Synthesis Engine with Strict Auditability

Built a customized contract intelligence pipeline processing 12,000+ cross-border master service agreements with verifiable source-grounded references.

Verified Technical Stack
LangGraphNeo4j GraphDBvLLMPostgreSQLDocker Swarm
Review Cycle Acceleration
81%
from 18h to 3.4h
Clause Omission Rate
0.0%
verified zero missing
Contract Throughput
12.5k
per fiscal quarter
Engineering Challenge:

Commercial lawyers spent 18+ hours reviewing dense counterparty redlines with generic LLMs frequently missing domain-specific liability indemnification clauses.

Architectural Intervention:

Formulated a structured graph-based semantic parsing system that extracts clause dependencies, validates against proprietary playbook rules, and exposes step-by-step reasoning.

Autonomous Agent WorkflowsSector: Supply Chain & Logistics
Production Active

Multi-Agent Exception Remediation & Freight Re-Routing

Designed an autonomous multi-agent mesh capable of intercepting port customs delays, negotiating alternative freight lanes, and executing dynamic schedule updates.

Verified Technical Stack
AutogenRedis QueueTemporal.ioPython 3.12Kubernetes
Autonomous Resolution
73%
zero manual inputs
Mean Triage Latency
4.5m
down from 48 hours
Demurrage Penalty Reduction
$1.8M
annualized savings
Engineering Challenge:

Unplanned disruptions created 48-hour routing deadlocks, requiring manual operational triage and leading to substantial demurrage penalties.

Architectural Intervention:

Constructed a stateful agent collective equipped with strict deterministic state machines, human-in-the-loop approval thresholds, and automated carrier API negotiation adapters.

High-Throughput InferenceSector: Real-Time Fraud Telemetry
Production Active

Sub-15ms Speculative Decoding & Quantized Model Serving

Optimized a 70B parameter anomaly detection model suite down to sub-15ms inference latency on clustered GPU nodes, sustaining 14,000 requests per second.

Verified Technical Stack
TensorRT-LLMTriton ServerCUDA C++Ray ServePrometheus
P99 Batch Latency
14.2ms
-82% latency drop
Peak Query Throughput
14.8k
req/sec sustained
Compute Cost Reduction
62%
$420k/yr cloud saved
Engineering Challenge:

Massive inference compute costs and unpredictable queue spikes caused transaction timeouts during high-velocity holiday e-commerce surges.

Architectural Intervention:

Applied dynamic FP8 kernel quantization, continuous batching engines, and speculative draft models to achieve 4.8x higher throughput on identical GPU hardware.

12-Person Multi-Disciplinary AI Engineering Firm

Have a complex enterprise AI roadmap to validate?

Speak directly with our senior technical partners. We review your architecture, latency constraints, and deployment topology before scoping.

Verified Enterprise Outcomes

Architectural leadership evaluated by engineering outcomes.

Enterprise leaders and technical directors discuss the measurable performance, governance rigor, and latency gains delivered by SUDO's 12-person senior AI consulting team.

Infrastructure & Compute
-68%
Inference Latency Reduction

SUDO's 12-person specialized team diagnosed and re-architected our distributed model serving cluster in under six weeks. Their direct access to senior practitioners eliminated typical agency overhead.

Scope: Distributed LLM Cluster Optimization
David Vance
VP of Engineering
Aegis Financial Systems
Enterprise Governance
100%
HIPAA & SOC 2 Compliance Validation

Implementing generative AI workflows across clinical records required strict isolation. SUDO formulated our compliance guardrails and custom evaluation harnesses with uncompromising technical precision.

Scope: Air-Gapped Private Model Governance
Elena Rostova
Chief Information Security Officer
Helios Health Data
Production Deployment
4.2x
Throughput Acceleration

Most consultancies provide theoretical roadmaps. SUDO deployed production-grade Triton inference engines and quantized models directly into our telemetry pipelines, cutting runtime GPU costs significantly.

Scope: Multi-Region Edge AI Pipeline
Marcus Sterling
Head of AI Architecture
Novus Logistics Global
Infrastructure & Compute
$1.4M
Annual Cloud Compute Savings

The engineering depth SUDO brought to our memory-bound transformer architectures delivered measurable fiscal and performance outcomes on week one. They are our trusted technical partner.

Scope: vLLM & TensorRT Backend Integration
Sophia Chen
Director of Machine Learning
Vektor Autonomous Systems
Enterprise Governance
99.98%
Deterministic Model Output Rate

In high-frequency algorithmic evaluation, hallucinations are fatal. SUDO built deterministic validation layers and audit mechanisms that allowed our executive board to greenlight production launch.

Scope: Financial Risk Verification Harness
Jonathan Cole
Managing Director of Technology
Stanton Capital Markets
Production Deployment
18 Days
Zero-Downtime Migration Window

SUDO managed the migration of our legacy recommendation systems to an active-active vector database cluster with zero customer downtime. Their 12-person focus provided unmatched agility.

Scope: Vector Search Production Cutover
Kavita Patel
SVP Platform Operations
Synthetix Retail Core
Direct Consulting Bandwidth Available

Discuss your AI architecture with our senior engineering team.

Connect directly with our 12-person specialist practice to review infrastructure benchmarks, deployment pipelines, and custom governance models.