Bringing intelligence
into everything
we build and
everything we build with
documents processed
vehicles 30M pts/min
live sports events / yr
OT assets monitored
Stats you can watch - AI-physics proof clips
Turn engineering drawings into engineering intelligence
A living twin of human organs, built from a single CT scan
Vision Al reading at 100 km/h
Where generic AI stops.
What 300 engineering leaders told us
• 16 industries
EI learns from the entire engineering lifecycle
from concept and design to validation, deployment and operations.
The intelligence generic AI never sees.
Design
CAD · Schematics ·
Requirements · Models
Build
Source code · Test results ·
Simulations · Twins
Operate
Telemetry · Logs · Field
Performance · Service Records
Govern
Standards · Compliance ·
Certifications · Knowledge
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The Engineering
Intelligence
<a href="https://www.ltts.com/solutions/EIOne" target="_blank"><span class="ei-campaign-title-aqua">100+ EI SOLUTIONS</span></a><br>across engineering, products and operations
- TrackEi Rail Inspection
- EdgeVisionVision Compute
- Off-Highway Control Autonomous Machines
- Patient Monitoring Suite Speech & Sound AI
- Chest-rAi Clinical Decision Support
- HumanSense Worker Safety
- LightsOutFactory Autonomous Manufacturing
- HumanNoids Industrial Robotics
- EnergiSense Energy & Emissions
- Asset Health Asset Reliability
- LTwinDigital Twin
- AMRVision Autonomous Field Ops
Our AI sits exams
generic AI
has never heard of.
Delivered by 2,000+ Forward-Deployed Engineers.
Plant Engineering
Mobility
Healthcare
Industrial products
We engineer ecosystems
From the grid to the chip
From the grid to the chip, we engineer
every layer of the data center.
From silicon to intelligence in motion
From silicon to intelligence in motion,
we engineer every layer of the software-defined vehicle
From bare earth to the first molecule
From bare earth to the first molecule,
we engineer every layer of the plant lifecycle
From stadium to the screen
From stadium to the screen,
we engineer every layer of the media chain
Outcomes across the physical economy.
Engineering Intelligence
at work
EI in Concept & FEED
Know what a plant will really cost,
and why, before anyone commits the capital.
EI in Engineering
Drawings and models produced in hours,
checked against every rule before anyone builds.
EI in Operations
Understand why the plant behaves the way it does,
then run it at its best every day.
EI in Engineering
Designing and proving vehicles faster,
without cutting a single safety corner.
EI in Products
Intelligence that ships inside the vehicle,
so it keeps getting better after it leaves the plant.
EI in Operations
Every train, fleet and aircraft inspected,
and tested by machines that never look away.
EI in Engineering
From idea to approval faster,
with the evidence trail regulators expect.
EI in Products
Intelligence inside the device that helps the clinician decide,
and never decides for them.
EI in Manufacturing
Catch the defect on the line, not in the field,
on every batch you make.
EI in Production
A factory that makes its own routine decisions,
with people supervising instead of operating.
EI in Supply Chain
See what every part should cost, where it is,
and what is about to go wrong.
EI in Assets & Energy
Machines that ask for maintenance before they stop,
and use less energy doing it.
EI in Engineering
Design the panel, generate the control code,
catch the error long before it reaches site.
EI in Products
Control that thinks on the edge,
so the line keeps running whether the cloud is there or not.
EI in Operations
Balance generation, storage and demand across the grid,
and find the fault before anyone loses power.
EI in Engineering
Your app tested on every phone, TV and set-top box,
before a viewer finds the fault.
EI in Products
Launch a streaming service, run live sport on it,
and make sure every ad actually plays
EI in Operations
Every channel, stream and ad monitored around the clock,
and fixed before your audience notices
EI in Engineering
5G and 6G products through testing and certification faster,
in labs that run themselves.
EI in Networks
Networks that find their own faults and name the cause,
not just the symptom.
EI in Operations
See tomorrow's failure today,
and fix the site before a single customer notices.
EI in Engineering
Software built with intelligence at its core,
from the first line of code.
EI in Platforms
Your CRM, service desk and
customer platforms act on what they already know.
EI in Operations
Every AI agent you run,
accounted for: what it costs, what it does, whether it works.
EI Library
244 AI patents filed and
put to work inside the platforms
81
- Reading P&IDs & Engineering Drawings
- Borderless Table Extraction
- CAD Generation from AI Models
- Domain-Based OCR Correction
- Document Quality Scoring
- 2D Views from 3D CAD
32
- Compressing Neural Networks
- Pruned & Quantized LLMs
- LLMs on Constrained Devices
- Memory-Optimized MoE Inference
- Teacher-Student Distillation
- Model Verification
30
- Domain-Specific Tokenizers
- Fusing Expert LLMs
- LLM Selection per Query
- Prompt Validation & Control
- Natural Language to SQL
- Code-Generation Query Optimization
26
- Rail Defect Detection
- Point-Anomaly Detection
- Contour Completion
- Glare & Specular Correction
- Real-Time Object Classification
- Deepfake Prevention
26
- Auto-Generating & Fixing Test Cases
- Early Failure Prediction
- Log-Error Detection
- EOL Component Replacement
- Emissions Compliance Validation
- AI-Designed Power Electronics
18
- X-Ray Analysis & Reporting
- AI Endoscope Navigation
- Blood-Smear Analysis
- NAFLD Staging from Images
- Post-Operative Imaging
- Condition-Growth Monitoring
81
- Reading P&IDs & Engineering Drawings
- Borderless Table Extraction
- CAD Generation from AI Models
- Domain-Based OCR Correction
- Document Quality Scoring
- 2D Views from 3D CAD
32
- Compressing Neural Networks
- Pruned & Quantized LLMs
- LLMs on Constrained Devices
- Memory-Optimized MoE Inference
- Teacher-Student Distillation
- Model Verification
30
- Domain-Specific Tokenizers
- Fusing Expert LLMs
- LLM Selection per Query
- Prompt Validation & Control
- Natural Language to SQL
- Code-Generation Query Optimization
26
- Rail Defect Detection
- Point-Anomaly Detection
- Contour Completion
- Glare & Specular Correction
- Real-Time Object Classification
- Deepfake Prevention
26
- Auto-Generating & Fixing Test Cases
- Early Failure Prediction
- Log-Error Detection
- EOL Component Replacement
- Emissions Compliance Validation
- AI-Designed Power Electronics
18
- X-Ray Analysis & Reporting
- AI Endoscope Navigation
- Blood-Smear Analysis
- NAFLD Staging from Images
- Post-Operative Imaging
- Condition-Growth Monitoring
It takes an ecosystem
to engineer intelligence
We work with the leaders at every layer of the market -
and engineer them into one intelligent system
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SILICON
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DATA
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ENGINEERING PLATFORMS
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GOVERNANCE & CLOUD
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UNIVERSITIES
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Go deeper
A LTTS AND MIT MEDIA LAB PARTNERSHIP
How ready is your engineering organization for AI?
A five-imperative readiness framework, scored with your leadership in a working session, benchmarked against 100+ engineering organizations.
LTTS defines Engineering Intelligence as the systematic infusion of human and machine intelligence into the engineering work, into the product that work produces, and into the plant that builds it. It spans engineering, products and manufacturing operations, combining agentic AI, physical AI and digital twins with deep domain expertise. In LTTS's own shorthand, EI means bringing intelligence into everything it builds and everything it builds with: a capability its engineers work with, and an outcome its clients ship.
LTTS builds Engineering Intelligence for engineering work, not general business tasks. Generic models learn from the open internet; EI platforms are pretrained on industry engineering data, targeting 75-85% baseline accuracy before any client-specific tuning. They understand requirements, BOMs, test suites and safety standards, so every output is traceable to an engineering reason.
LTTS delivers Physical AI as intelligence running inside the product or machine itself, within real power, latency and safety limits. Yes, it runs at the edge with no cloud dependency: EIOne's patent-backed pruning and quantization compress models for full-accuracy inference on constrained hardware. One industrial customer achieved wood-saw blade retraction in 18 to 24 milliseconds using an AI-native chip and vision language model, in production.
LTTS builds EI digital twins as live, physics-informed replicas that keep learning from real operating data; traditional simulation is a one-off model run before build. That difference shows up in results: LTwin's physics-informed neural networks reached close to 90% accuracy in predicting early-stage mechanical cracks and cut testing timelines by approximately 75%.
LTTS makes AI auditable by producing the evidence trail alongside the engineering work, not after it. Every agent action, reasoning step and output is traced and logged, and validation artefacts map to the standard that governs the product: ISO 26262 and ISO/PAS 8800 for automotive, DO-178C for aerospace, IEC 62304 and FDA frameworks for medical devices.
LTTS has Engineering Intelligence running in production across industries. Delivered outcomes include 95% less test-scripting effort (193 man-days completed in 10), over 85% accuracy in early aircraft fault prediction, more than 80% fewer unplanned plant incidents, and traceable ESG data across 1,000+ sites that helped a client raise $100 Mn in green bonds.
LTTS Engineering Intelligence spans three domains: Engineering (design, modelling, code and compliance), Products (embedded, edge and silicon AI), and Manufacturing & Operations (plant, asset and field). It includes 100+ solutions such as PLxAI, AiStudio, Ainfonix, LTwin and LightsOutFactory, orchestrated through EIOne, the agentic AI platform, and backed by 244+ AI patents.
LTTS EI Agents are autonomous multi-agent workflows that plan, act and complete engineering tasks end to end, built and run on EIOne. Governance is built in: role-based access, approval gates, runtime guardrails, and end-to-end tracing with step-level reasoning logs, so every action is auditable. EIOne runs on-premises or in your private cloud, so proprietary engineering IP never leaves your environment.
LTTS applies Engineering Intelligence across plant, asset and field operations: connected machines, autonomous manufacturing, asset reliability, energy and emissions, and supply chain. Real deployments include 152 plants brought into one operating system with zero production downtime during rollout, and predictive asset health across 22 plants that saved one client ~$10 Mn in year one.
LTTS deploys AI in safety-critical industries every day, and the rule is simple: existing safety standards remain the compliance regime whether or not AI is involved. LTTS designs to a human-in-the-loop default, so even where a system can act autonomously, an engineer verifies at the decision threshold. That is what makes AI acceptable to regulators in medical devices, automotive and aerospace.
LTTS builds Engineering Intelligence on the platforms you already run. EI integrates across silicon (NVIDIA, SiMa.ai, Qualcomm), models (Anthropic), data (Databricks, Cognite), engineering platforms (PTC, AVEVA, Dassault Systèmes, Siemens, Honeywell) and cloud (AWS, Azure). EIOne workflows can also be exported and deployed in your own native environment, with no forced data movement.
LTTS assesses AI readiness using the Enterprise AI Readiness Index, built with the MIT Media Lab, which measures your capacity to change workflows and governance rather than counting tools. LTTS then maps you against its six-layer EI architecture, from data readiness to intelligent outcomes, and recommends starting with one high-friction workflow: pilot with your experts in control, then scale what proves value.