MINOVATIVE
AI Innovation Lab

Where AI Research
Meets Production Reality

Minovative's AI Lab bridges cutting-edge research and enterprise deployment. We build, test, and ship production-grade AI systems — LLMs, computer vision, predictive models, and autonomous agents — across every major industry.

ai-lab / inference-engineLIVE
LLM · GPT-4o-mini340ms
Contract summarisation
Vision · YOLOv942ms
Defect detection — Line 4
NLP · BERT-Large88ms
Sentiment analysis batch
Forecast · XGBoost19ms
Demand planning — SKU 1.2K
Agent · LangGraph1.8s
Support ticket resolution
14,280
Requests/min
23
Active Models
94.8%
Avg Accuracy
Core Capabilities

Every AI Discipline. One Lab.

From language understanding to autonomous decision-making — our researchers and engineers cover the full AI spectrum.

Large Language Models

Fine-tune and deploy LLMs for domain-specific tasks — document understanding, Q&A, summarisation, code generation, and enterprise chatbots grounded in your own knowledge base.

GPT-4oLLaMA 3MistralRAGFine-tuning

Computer Vision

Real-time object detection, image classification, OCR, and video analytics pipelines deployed at the edge or cloud. From quality inspection on the factory floor to retail shelf monitoring.

YOLOv9SAM 2CLIPOCREdge AI

NLP & Text Intelligence

Extract structure from unstructured text — entity recognition, sentiment analysis, document classification, contract review, and multi-language support across 50+ languages.

NERSentimentClassificationTranslationMultilingual

Predictive Analytics

Forecasting models for demand planning, churn prediction, fraud detection, and maintenance scheduling — trained on your historical data with explainability built in.

Time SeriesXGBoostSHAPAutoMLForecasting

Generative AI

Build production GenAI products — AI copilots, content generation pipelines, synthetic data generation, and multi-modal apps combining text, image, and audio.

Stable DiffusionDALL-E 3CopilotsSynthetic DataMulti-modal

Agentic AI Systems

Design and deploy autonomous AI agents that plan, reason, use tools, and execute multi-step workflows — from research agents to fully autonomous process automation.

ReActLangGraphAutoGenTool UseMulti-agent
Case Studies

Projects From the Lab

Real deployments built by Minovative's AI Lab — from proof-of-concept to full production.

Live

Supply Chain Demand Forecaster

Retail & Logistics

Ensemble time-series model combining SARIMA, XGBoost, and an LSTM to forecast 90-day product demand across 1,200+ SKUs. Deployed on AWS SageMaker with a drift-detection monitor.

94.3%
Forecast Accuracy
1,200+
SKUs Covered
120ms
Latency p99
Time SeriesAWS SageMakerPythonMLflow
Live

Document Intelligence Platform

Finance & Legal

LLM-powered pipeline that ingests PDFs, contracts, and invoices — extracts key clauses, entities, and amounts — then stores structured data in a searchable knowledge graph.

50K/day
Doc Processing
97.1%
Entity Accuracy
70%
Cost Reduction
RAGLlamaIndexGPT-4oNeo4j
Live

Visual Quality Inspection

Manufacturing

Edge-deployed computer vision system that detects surface defects on production lines with sub-100ms inference. Integrates with existing SCADA systems via OPC-UA.

99.4%
Defect Detection
0.3%
False Positive Rate
42ms
Inference Time
YOLOv9ONNXEdge AIOPC-UA
Beta

Autonomous Customer Agent

Telecom & SaaS

Multi-step agentic system that resolves Level-1 support tickets end-to-end — reads tickets, queries internal APIs, executes remediation actions, and escalates with context when needed.

68%
Ticket Deflection
4.6 / 5
CSAT Score
< 2 min
Avg Resolution
LangGraphGPT-4oTool UseZendesk API
Research Focus

Active Research
Programmes

Our Lab teams don't just implement existing techniques — they push boundaries. We publish research, contribute to open source, and bring frontier findings into our client work.

Accepted papers at NeurIPS, ICML, ACL
12 open-source model checkpoints published
Active contributors to HuggingFace & LangChain
Quarterly AI research briefings for clients

AI Safety & Alignment

Interpretability research, RLHF techniques, and red-teaming frameworks to build trustworthy AI systems.

Foundation Model Research

Exploring efficient pre-training, LoRA fine-tuning, and domain adaptation for enterprise LLMs.

Edge AI & Quantization

Model compression, INT8/FP16 quantization, and ONNX export pipelines for edge and mobile deployment.

Multi-modal Learning

Unified embeddings across text, image, and audio for richer cross-domain understanding and retrieval.

MLOps & Observability

Data and model drift detection, automated retraining pipelines, and experiment tracking at scale.

Privacy-Preserving AI

Federated learning, differential privacy, and confidential computing for sensitive enterprise data.

Our Process

From Idea to Deployed AI

A proven 4-step framework that turns your AI opportunity into a production system — fast.

01

Discovery & Scoping

We map your business problem to AI capabilities, audit your data assets, and define success metrics before any code is written.

02

Rapid Prototyping

2–4 week sprint to build a working proof-of-concept using your data. Validated against real performance benchmarks.

03

Iterative Training

Model fine-tuning, hyperparameter search, and evaluation loops until target accuracy and latency are achieved.

04

Production Deployment

CI/CD pipelines, A/B testing, canary releases, and monitoring dashboards — from notebook to production in weeks.

Tech Stack

Our AI Toolchain

Best-in-class tools across every layer — from training to inference, orchestration to observability.

PyTorchTraining
TensorFlowTraining
JAX / FlaxTraining
HuggingFaceModels
LangChainOrchestration
LangGraphOrchestration
LlamaIndexRAG
AWS SageMakerMLOps
MLflowMLOps
RayCompute
ONNXInference
TritonInference
WeaviateVector DB
QdrantVector DB
Apache KafkaStreaming
AirflowPipelines
dbtTransform
GrafanaMonitoring

Have an AI Problem to Solve?

Whether you're starting your AI journey or scaling an existing capability, our Lab team will scope, build, and ship a solution designed for your data and your goals.

Start a Conversation Explore AI Solutions
2-week rapid prototype
Production-ready in 6–10 weeks
Dedicated AI research team
Ongoing model monitoring