AI SOFTWARE DEVELOPMENT

Practical AI software built around real business workflows.

NovCleda helps businesses design, build, and integrate AI systems that reduce repetitive work, improve access to information, and add useful intelligence to existing products and operations.

novcleda-ai-runtime://cluster-us-east
ACTIVE·38MS
POST /api/v1/agent/orchestrate
Input: Unstructured User Intent + Context Payload
Payload Verified
NovCleda Agent Orchestration Core
3 Sub-Agents Active
Analyzer
Context: 98%
Executor
Tool Calling
Validator
Schema Match
STATUS 200 OK
Latency: 42ms · Zero Data Retention · Guardrails Enforced
Human-in-Loop: Verified
➜model: gpt-4o / claude-3-5-sonnet
Technical Capabilities

AI capabilities engineered for performance

We deliver modular AI components designed for reliability and seamless API integration.

AI Agents & Assistants

Autonomous task-solving agents that execute complex multi-step workflows.

AI Workflow Automation

Custom n8n and API orchestration connecting operational business applications.

Document Intelligence

Automated document parsing, data extraction, and structured classification.

AI Search & Knowledge Systems

Vector search (RAG) providing instant retrieval across your internal company docs.

Predictive Analytics

Machine learning models predicting demand, churn, and operational trends.

Computer Vision

Visual classification, image inspection, and automated document analysis.

AI Integrations

Seamless API integration with OpenAI, Anthropic, Gemini, and open-source models.

Data Pipelines

Clean data ETL pipelines, embeddings generation, and vector store management.

Developer-First Architecture

Type-safe SDKs and modular API orchestration

Our AI software exposes clean REST and Python/TypeScript SDK endpoints. Connect document parsing pipelines, autonomous task routers, and private vector stores into your existing codebase without complex dependencies.

agent_orchestrator.py
# NovCleda AI Agent SDK - Production Dispatch
from novcleda_ai import AgentCluster, RAGVectorPipeline

cluster = AgentCluster(api_key="nc_live_9941a8")
pipeline = cluster.connect_rag(collection="enterprise_contracts")

response = await cluster.dispatch_task(
    workflow="invoice_audit_and_reconciliation",
    input_payload={"pdf_uri": "s3://finance/inv_8820.pdf"},
    confidence_threshold=0.95,
    human_in_the_loop=True
)

print(f"Status: {response.status} | Time: {response.latency_ms}ms")
Production Ready · Zero Cloud Lock-in
Operational Impact

Where AI creates business value

High-leverage operational areas where AI automation delivers immediate productivity gains.

Customer Support

Intelligent triage, automated answers, and agent assist.

Back-Office Operations

Invoice processing, data entry, and record validation.

Document Processing

Contract analysis, PDF extraction, and summary generation.

Internal Knowledge

Instant enterprise document search across manuals & SOPs.

Sales Workflows

Lead enrichment, communication summarization, and follow-ups.

Automated Reporting

Executive metric summaries generated from raw operational data.

Operations Monitoring

Anomaly detection and proactive system notification workflows.

Pragmatic AI Framework

AI Readiness Assessment

Before deploying models, we evaluate 6 practical pillars to ensure your organization is positioned for successful AI software implementation.

Business Problem

A clear operational bottleneck or product capability requirement.

Available Data

Structured or unstructured data sources ready for ingestion.

Existing Systems

Clean APIs or database access points for integration.

Security Scope

Defined data privacy, access controls, and compliance boundaries.

Human Review

Human-in-the-loop verification rules for critical decisions.

Success Metrics

Measurable ROI targets (time saved, speed, accuracy).

Start with the problem, not the algorithm

Successful AI implementation starts by identifying measurable human friction. Whether automating document parsing or training custom RAG pipelines, NovCleda focuses strictly on code that works in production.

Execution Method

Our 9-step AI delivery process

A methodical engineering pipeline designed for accuracy, security, and smooth deployment.

Active Pipeline Stage: Step 01 — Discover
01In Progress

Discover

We audit your workflow to pinpoint where AI creates genuine ROI.

02Stage 2

Feasibility

We validate data availability, model accuracy, and latency constraints.

03Stage 3

Prototype

We build a fast working prototype to verify model performance.

04Stage 4

Architecture

We design secure API contracts, database schemas, and data pipelines.

05Stage 5

Development

Our engineers build clean, maintainable backend and frontend code.

06Stage 6

Integration

We connect AI modules smoothly into your CRM, ERP, or web app.

07Stage 7

Testing

Rigorous testing for edge cases, prompt safety, and benchmark accuracy.

08Stage 8

Deployment

Production release with monitoring, rate limits, and fallback rules.

09Stage 9

Improvement

Continuous feedback loop refinement, model updates, and optimization.

Supported Technologies

Realistic AI & engineering stack

We build using battle-tested frameworks, proven LLM APIs, and maintainable cloud architectures.

OpenAI GPT-4o
Anthropic Claude 3.5
Google Gemini 1.5
Meta Llama 3
PyTorch 2.4
Next.js 15
TypeScript
Python 3.12
Pinecone Vector DB
n8n Workflow Core
LangChain
FastAPI
AWS Bedrock
Docker Containers
PostgreSQL
Redis Cache
OpenAI GPT-4o
Anthropic Claude 3.5
Google Gemini 1.5
Meta Llama 3
PyTorch 2.4
Next.js 15
TypeScript
Python 3.12
Pinecone Vector DB
n8n Workflow Core
LangChain
FastAPI
AWS Bedrock
Docker Containers
PostgreSQL
Redis Cache

Models & LLM APIs

OpenAI GPT-4oAnthropic Claude 3.5Google Gemini 1.5Meta Llama 3Whisper Speech

Python & AI Frameworks

Python 3.12PyTorchLangChainLlamaIndexFastAPI

Application Layer

Next.js 15 App RouterReact 19TypeScriptNode.jsTailwind CSS

Data & Vector Stores

PostgreSQLPgVectorPinecone Vector DBRedis Cache

Cloud & Infrastructure

AWS BedrockDocker ContainersVercel EdgeGoogle Cloud PlatformCloudflare Workers

Workflow Automation

n8n WorkflowsGraphQL ServicesFastAPI WebhooksNode.js Pipelines
System Connectivity

Seamless integration with existing software

You don't need to rebuild your technology stack to leverage AI. We integrate directly.

CRM Systems

CRM Systems

Salesforce · HubSpot · Custom

ERP Systems

ERP Systems

SAP · NetSuite · Odoo

Web Applications

Web Applications

Next.js · React · Node.js

Mobile Applications

iOS · Android · Cross-platform

Internal Admin Tools

Dashboards · Portals · Intranets

REST & GraphQL APIs

Custom · OpenAPI · Webhooks

Vector Databases

Pinecone · pgVector · Weaviate

n8n Automation

Workflow · Triggers · Webhooks

Enterprise Control

Security, compliance & human governance

AI systems built with transparent guardrails, data privacy, and human oversight.

Granular Permissions

Strict role-based access control protecting sensitive data.

Data Minimization

Only sending required context to model endpoints without storing raw PII.

Complete Auditability

Comprehensive logging of all AI prompts, responses, and token usages.

Human-in-the-Loop

Automated workflows requiring human confirmation for critical actions.

Validation & Fallbacks

Strict output schema validation and graceful fallback logic.

System Monitoring

Real-time performance tracking for response times, accuracy, and cost.

AI Implementation FAQ

Frequently asked questions about AI development

Clear answers about data privacy, model selection, integrations, and ongoing support.

If your team spends significant time on repetitive data entry, document processing, customer inquiries, or searching across scattered internal files, your business will benefit from practical AI automation.
Yes. We connect AI models and RAG search directly to your existing PostgreSQL, MySQL, or enterprise databases via secure APIs without requiring a complete database rewrite.
Basic automation follows rigid rules (if A then B). An AI agent can interpret unstructured input, analyze context, select tools, and handle multi-step decisions dynamically.
We enforce enterprise data privacy agreements, utilize zero-retention API endpoints, host open-source models on private cloud infrastructure when required, and restrict model access via strict RBAC controls.
No. Most business AI implementations (such as document intelligence, n8n workflows, and RAG knowledge bases) work effectively with your existing company docs, SOPs, and APIs.
We provide ongoing software maintenance, monitor output accuracy, update prompt templates, and refine model performance as your operational data grows.
Let’s Work Together

Not sure where AI fits yet?

Start with the workflow or business problem, not the model.