AI Engineering Enterprise Ready

AI Development Services

Build AI applications that solve real business problems and work inside your existing technology environment.

Our AI development services cover machine learning, language AI, generative AI, intelligent automation, computer vision, document intelligence and enterprise AI applications — from solution design through production deployment.

Proven AI Delivery

300+ AI Deployments50+ AI Projects Delivered400+ AI Specialists98% On Time Delivery

Trusted by Fortune Global 500 leaders, governments & top universities across 30+ countries

PatangPatang
Transworld GroupTransworld Group
OrangeOrange
Arbor Financial GroupArbor Financial Group
PetronasPetronas
FibeFibe
CetuCetu
University of UtahUniversity of Utah
Arizona State UniversityArizona State University
Kiss USAKiss USA
RoofAid USARoofAid USA
Edgerton StrategiesEdgerton Strategies
University of TorontoUniversity of Toronto
FujitsuFujitsu
Teka GroupTeka Group
ISKCONISKCON
Transworld JetsTransworld Jets
Port of FujairahPort of Fujairah
AD Ports GroupAD Ports Group
Royal Commission for AlUlaRoyal Commission for AlUla
Makani Community CentersMakani Community Centers
Abu Dhabi DMTAbu Dhabi DMT
MAIR GroupMAIR Group
AdcoopAdcoop
HuaweiHuawei

Powered by leading cloud & AI platforms

AWSAWS
Google CloudGoogle Cloud
Microsoft AzureMicrosoft Azure
NVIDIANVIDIA
OpenAIOpenAI
AnthropicAnthropic
GeminiGemini
GrokGrok
PerplexityPerplexity
Google AIGoogle AI

Recognized by leading industry reviewers

Awards & industry recognition

Top AI Development Company by Selected FirmsTop AI Development Company by Selected Firms
Top IT Consulting, SI & Managed Services Company by ITRateTop IT Consulting, SI & Managed Services Company by ITRate
Top Web Development Company by Selected FirmsTop Web Development Company by Selected Firms
Top Service Provider 2025 by RightFirmsTop Service Provider 2025 by RightFirms
Top App Development Company by AppDevelopmentCompaniesTop App Development Company by AppDevelopmentCompanies
Top Software Development Company by Selected FirmsTop Software Development Company by Selected Firms
Best Support Company 2025 by SoftwareSuggestBest Support Company 2025 by SoftwareSuggest
Top AI App Developers by C2C ReviewsTop AI App Developers by C2C Reviews

Recognition

Award-Winning AI Engineering

Recognized for enterprise AI delivery and custom artificial intelligence development.

Top AI Solutions Provider for Enterprises — 2025

Top AI Development Company by Selected Firms

Top AI Development Company by Selected Firms

Top AI App Developers by C2C Reviews

Top AI App Developers by C2C Reviews

Top IT Consulting, SI & Managed Services Company by ITRate

Top IT Consulting, SI & Managed Services Company by ITRate

Top Software Development Company by Selected Firms

Top Software Development Company by Selected Firms

Reviewed on Clutch, GoodFirms, Selected Firms and DesignRush.

Capabilities

Custom AI Development Services

Build AI around your business workflows, data and users rather than forcing your operations into a generic platform.

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Solutions

AI Solutions We Build

The shapes an AI project usually takes once the business problem is clear.

Forecast

Predictive AI

Use historical and operational data to forecast outcomes, identify risk and support better decisions.

Automate

Intelligent Automation

Use AI to classify, extract, analyze or interpret information inside existing business workflows.

Assist

AI Assistants

Build customer-facing and internal assistants that help users work with information and software through natural language.

Extract

Document Intelligence

Extract, classify and validate information from invoices, forms, contracts and other business documents.

Decide

Decision Intelligence

Combine predictive models, business rules and human oversight to support operational decisions.

Embed

AI-Enabled Products

Add artificial intelligence directly into customer-facing software and digital products.

Process

From AI Idea to Production

AI development should end with a system that works in production — not only a prototype.

01

Discover

Define the business problem, users, data and success criteria.

02

Design

Select the appropriate AI approach and define the application architecture.

03

Build

Develop the models, application services and required interfaces.

04

Integrate

Connect the solution with existing systems, data and workflows.

05

Evaluate

Test quality against representative business scenarios.

06

Deploy

Release the application into the required environment.

07

Improve

Monitor performance and refine the system using production evidence.

Architecture

AI Development Architecture

A production AI application typically combines several layers.

Layer 01

Application Layer

Deliver AI through websites, enterprise software, mobile applications, internal portals or APIs.

Layer 02

AI Layer

Use the appropriate model or AI service for the specific workload.

Layer 03

Data Layer

Provide approved business information required by the application.

Layer 04

Integration Layer

Connect AI with CRM, ERP, databases, APIs and other operational systems.

Layer 05

Validation

Apply deterministic rules, confidence thresholds and human review where needed.

Layer 06

Monitoring

Track operational quality, latency, failures, usage and business outcomes.

By Function

AI Development by Function

Where AI tends to earn its place first inside an organization.

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Operations

Operations

Automate document-heavy tasks, exception handling, classification and operational analysis.

Finance

Finance

Support forecasting, risk analysis, reporting and intelligent document workflows.

Service

Customer Service

Build conversational support, request routing and knowledge-assisted service applications.

Sales

Sales

Support lead qualification, account research, summaries and CRM workflows.

IT

IT

Use AI for internal support, service management and enterprise knowledge access.

Product

Product Teams

Add AI capabilities directly to software products and customer experiences.

By Industry

AI Development by Industry

Sector patterns we build against most often.

Finance

Financial Services

Fraud detection, risk scoring, document intelligence and controlled AI workflows.

Health

Healthcare

Administrative automation, document processing, intelligent assistance and operational AI.

Logistics

Logistics

Shipment intelligence, document automation, forecasting and operational decision support.

Industry

Manufacturing

Visual inspection, predictive maintenance, technical assistance and process intelligence.

Commerce

Retail and E-Commerce

Recommendations, forecasting, customer experience and generative content.

Impact

Nonprofits and NGOs

AI-enabled ERP, workflow automation, reporting and organizational productivity.

Stack

AI Technology Stack

Chosen for the workload, not for the newest model on the market.

AI and Machine Learning

Where the modelling happens

  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Hugging Face

Language AI

Model families we build on

  • OpenAI
  • Claude
  • Gemini
  • Llama
  • Mistral

AI Engineering

How capability becomes an application

  • LangChain
  • LangGraph
  • FastAPI
  • Node.js
  • REST APIs

Data

Where business information lives

  • PostgreSQL
  • MongoDB
  • Snowflake
  • Databricks

Infrastructure

Where it runs

  • AWS
  • Microsoft Azure
  • Google Cloud
  • Docker
  • Kubernetes
OpenAIOpenAI
ClaudeClaude
GeminiGemini
LlamaLlama
MistralMistral
Hugging FaceHugging Face
PyTorchPyTorch
TensorFlowTensorFlow
LangChainLangChain
LangGraphLangGraph
AWSAWS
AzureAzure
Google CloudGoogle Cloud
KubernetesKubernetes

Portfolio

AI Systems in Production

Real AI systems built around operational workflows and business outcomes.

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01 / 04 Case Study

Document IntelligenceSDLC Corp

2,000+Invoices Per Day
48 Hours → 4 HoursProcessing Time

Global Logistics

An AI document-processing workflow extracts information from invoices and bills of lading, validates important fields and sends approved results into enterprise operations.

DocumentExtractionValidationEnterprise Operations

  • Unstructured PDFs

  • Key field detection

  • Vendor information

  • Dates and amounts

  • Human-in-the-loop validation

  • ERP integration

Explore the Case Study
Transworld Logistics document processing platform extracting fields from unstructured invoice PDFs

Featured image from the Transworld document-processing case study.

02 / 04 Case Study

AI Virtual StagingSDLC Corp

~25 SecondsPer Render

Interior Design Platform

A generative AI application allows users to visualize furniture, flooring, wall finishes and lighting inside real rooms.

The production pipeline combines image understanding, real-scale visualization and generative models.

Room PhotoScene UnderstandingReal-Scale PlacementGenerated View

  • Image understanding

  • Inch-accurate scale

  • Furniture placement

  • Wall and floor finishes

  • Lighting

  • Usage-based rendering

Explore the Case Study
AI interior staging platform rendering furniture and finishes inside a real room photograph

Featured image from the DYD interior-design case study.

03 / 04 Product

Natural Language Call IntakeSDLC Corp

Pulastya AI

AI understands caller intent, captures relevant context and routes conversations into defined business workflows while preserving human handoff.

ConversationIntentStructured CaptureRoutingHandoff

  • Natural-language understanding

  • Intent classification

  • Structured request capture

  • Caller-context extraction

  • Workflow routing

  • Human handoff

Explore Pulastya
Pulastya AI call intake showing the detected intent and the matched queue before routing

Featured image from the Pulastya call-intake case study.

04 / 04 Product

Document AI PlatformSDLC Corp

18+Supported Document Types

Data AI Ninja

A document-intelligence platform classifies uploaded files, extracts structured information and provides confidence-based review workflows.

UploadClassificationExtractionConfidence ReviewStructured Output

  • Document classification

  • Language detection

  • Field detection

  • Confidence scoring

  • Reviewer validation

  • Audit log

Explore Data AI Ninja
Data AI Ninja document extraction console showing document type, detected language and per-field confidence

Featured image from the Data AI Ninja product page.

Client Stories

Real Stories. Real Impact.

Founders, CEOs, and operating leaders share what it's like to build with SDLC Corp.

What clients say01 / 05Listers Group
They approached our Salesforce discovery with real technical depth, uncovered structural gaps others missed, and delivered a solution that worked exactly as promised.
Listers Group
Chris GreenHead of Business, Listers Group
What clients say02 / 05Huawei
SDLC CORP built a mobile application that met our strategic requirements with strong technical execution. The solution performs reliably and has become an important operational asset.
Huawei
Abhinav PurohitChief Strategy, Huawei
What clients say03 / 05Reiss
They saw inefficiencies in our Salesforce workflow and redesigned our entire quote-to-cash system. We now operate faster, cleaner, and with better accuracy.
Reiss
Emma TaylorVP, Reiss
What clients say04 / 05Eye Fuze
From planning to post-launch, SDLC Corp guided us every step of the way. Their support makes them more than a vendor. They're a trusted partner.
Eye Fuze
Steve GrahamCEO, Eye Fuze
What clients say05 / 05Edgerton Strategies
The SDLC Corp team scaled our platform with impressive technical expertise, ensuring it's secure, robust, and ready for future growth.
Edgerton Strategies
Eric LeistCEO, Edgerton Strategies

Client story

Eric Leist

CEO, Edgerton Strategies

Edgerton Strategies

Doug Schmidt

CEO, Roofaid USA

RoofAid USA

Reyzal Razmi

All Star Influencers

All Star Influencers

By the Numbers

AI Engineering at Scale.

Delivery capacity behind the AI work.

3,400+Projects Delivered

across 12 industries

400+AI Specialists

Top 1% global talent

1,200+Global Engineers

across 6 continents

30+Countries Served

global regulatory regimes

300+AI Deployments

in production

10+ Yearsof Experience

in AI and software

Why SDLC Corp

Why Choose SDLC Corp

One team for the model, the application and the systems it has to live inside.

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End to End

End-to-End AI Engineering

Build the model, application, workflow and integration as one production system.

Depth

Specialist AI Teams

Use dedicated expertise across machine learning, language AI, RAG, agents, vision and generative AI.

Connected

Enterprise Integration

Connect AI with the software and systems already running your business.

Right-Sized

Model Flexibility

Select commercial, open or custom models according to the workload.

Measured

Production Evaluation

Measure AI against representative business scenarios before and after deployment.

Oversight

Human Oversight

Keep people involved where judgment, authorization or accountability is required.

Before You Build

Need AI Strategy First?

If the use case, architecture or investment priority is not yet clear, start with consulting before committing to implementation.

Related

Related AI Services

The governance, advisory and decision layers around AI development.

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Get Started

Build Your AI Solution

Turn a business problem into a production AI application that works with your users, data and existing systems.

Whether you need predictive models, language AI, intelligent automation, computer vision or a custom AI product, our engineering team can take the project from architecture through deployment.

Contact Us

Share a few details about your project, and we’ll get back to you soon.

Let's Talk About Your Project

FAQ

Frequently Asked Questions.

Straight answers on scope, technology choice, integration and how an AI project actually starts.

What are AI development services?

AI development services cover the design, engineering, integration and deployment of custom artificial intelligence applications.

Projects can include machine learning, language AI, computer vision, generative AI, intelligent automation and other AI capabilities.

What types of AI solutions do you build?

We build predictive systems, AI assistants, document intelligence applications, conversational AI, computer vision systems, generative AI products and enterprise AI workflows.

What is custom AI development?

Custom AI development means designing an AI application around a specific business problem, workflow, data environment and user requirement rather than using a generic off-the-shelf tool.

What is the difference between AI development and AI consulting?

AI consulting helps determine what should be built and why.

AI development turns the approved use case into a working application. See our AI Consulting Services.

What is the difference between AI development and AI integration?

AI development focuses on building the AI capability.

AI integration focuses on connecting that capability with existing business systems and production workflows. See our AI Integration & Implementation Services.

Do all AI projects require an LLM?

No. Many AI projects are better solved with traditional machine learning, computer vision, rules or specialized models.

The technology should follow the business requirement.

Can you build AI using our existing business data?

Yes. AI applications can use approved enterprise data when the required information is accessible, sufficiently reliable and appropriate for the intended use.

Can AI integrate with ERP and CRM platforms?

Yes. AI applications can connect with enterprise platforms through supported APIs, application services and native integration mechanisms.

Can AI be deployed privately?

Yes. Depending on the workload and models involved, AI applications can use managed cloud services, private cloud, customer-managed infrastructure or supported on-premise environments.

How do you evaluate an AI application?

Evaluation depends on the use case.

Measures can include prediction accuracy, extraction accuracy, response quality, latency, task completion, human escalation and business outcomes.

Can you improve an existing AI application?

Yes. We can review model performance, application architecture, data, integration, evaluation, latency, cost and production behavior to identify where improvements are needed.

How do we start an AI development project?

Start with a clearly defined business problem and measurable outcome.

From there, the project can assess data, choose the appropriate AI approach, define the architecture and validate the solution before production rollout.