SERVICES • ENGINEERING

AI & Machine Learning Development

Custom Large Language Models, deep learning systems, and robust MLOps pipelines designed for enterprise operations.

Overview

Artificial Intelligence and Machine Learning are no longer experimental features — they are critical engines driving operational efficiency, automated decision-making, and unparalleled user experiences. At Bitsapp, we build production-grade, secure, and highly scalable AI/ML solutions customized to your business goals. From tuning custom LLMs and training predictive regression models to orchestrating robust continuous retraining MLOps pipelines, we handle the full lifecycle of your data products. We implement models that solve real problems, ensuring clean APIs, low inference latency, and strict data governance.

Features

Custom Large Language Model (LLM) Fine-Tuning
Robust MLOps Pipelines (CI/CD for Machine Learning)
Computer Vision & Natural Language Processing (NLP)
Predictive Analytics & Recommendation Engines
Real-time Inference API Orchestration
Data Cleaning, Labeling & Feature Engineering

Benefits

Data-driven decision making and automation
Optimized operational cost and throughput
Intelligent, personalized user experiences
Robust and auditable model governance frameworks

Technologies

PyTorch TensorFlow Hugging Face LangChain OpenAI API LlamaIndex Kubeflow MLflow DVC Scikit-Learn Pandas NumPy Docker Kubernetes AWS SageMaker Google Vertex AI FastAPI Ray

Ready to build intelligent systems?

Connect with our AI engineers to discuss your data objectives and model architecture.

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Interactive Calculator

AI/LLM Inference Simulator

Tune parameter sizes, batching rules, and GPU clusters to estimate inference latency, memory requirements, and costs.

INFERENCE WORKLOAD EDITOR

13B
1B (Edge) 50B 100B (Enterprise Large)
16
1 (Real-time) 64 128 (High Batching)

PERFORMANCE HUB

45 TOKENS / SEC
SUITABLE DEPLOYMENT
Compute Metrics
OUR AI DEVELOPMENT PIPELINE

Our AI/ML Lifecycle Process

How we transform raw data into intelligent enterprise solutions.

01 Stage 1

Data Engineering

We curate, clean, and structure raw data pipelines, preparing high-quality features for training.

02 Stage 2

Model Selection & Architecture

We select optimal neural architectures, transformers, or classical models suited for your specific problem space.

03 Stage 3

Model Training & Tuning

We leverage accelerated computing environments to train models and execute hyperparameter optimization sweeps.

04 Stage 4

Evaluation & Validation

We validate models using strict cross-validation, checking bias, variance, and safety thresholds.

05 Stage 5

Deployment & Inference

We wrap models in scalable, low-latency API containers (like FastAPI) backed by auto-scaling GPU nodes.

06 Stage 6

MLOps & CI/CD

We deploy MLflow and Kubeflow pipelines to automate model testing, version control, and continuous integration.

07 Stage 7

Data & Concept Drift Monitoring

We establish telemetry to track model accuracy over time, triggering retraining when data drift exceeds thresholds.

08 Stage 8

SLA & Governance Support

Continuous model auditing, bias mitigations, cost optimizations, and security patches.

PIPELINE

Interactive AI/ML Production Pipeline

  1. 01

    Ingestion

    Data curation & streaming

  2. 02

    Preprocessing

    Labeling & feature store

  3. 03

    Training

    Neural network optimization

  4. 04

    Validation

    Accuracy & safety testing

  5. 05

    Serving

    Containerized REST/gRPC API

  6. 06

    Observability

    Drift & telemetry audit

System Architecture

Enterprise AI/ML Production Pipeline

A highly scalable, secure, and auditable MLOps lifecycle. From automated data cleaning and feature stores to distributed model training and zero-drift inference observability.

Scroll horizontally to view complete architecture
MLOPS INGESTION PREPROCESSING TRAINING VALIDATION SERVING OBSERVABILITY batch clean offline features online feature lookup (<10ms) orchestrates sweeps log metrics & artifacts candidate audits all gates pass → promote to prod certified model pull inference payloads operational metrics Continuous Retraining Feedback Loop (Orchestrates Spark Historical Lake Pull) 🗄 Data Lake AWS S3 / GCS 📥 Streaming Apache Kafka 📁 Versioning DVC / Lakehouse 🧶 Data Prep Apache Spark 👁 Validation Great Expectations 💾 Feature Store Feast (Offline & Online) Parquet & Redis Low-Latency 🧠 Training PyTorch / TensorFlow Distributed GPU Node 🎫 Hyper-Tuning Ray Tune / Optuna Bayesian Optimization 🏷 Model Registry MLflow Registry ✓ Certified Prod Artifacts ⚖ Bias / Fairness AIF360 Audit Toolkit 🛡 Robustness Test Adversarial Attack Simulation 📈 Benchmark F1 Score / Latency Profiler Triton Server Triton Inference Engine 🌐 API Serving FastAPI / gRPC Gateway ☯ Kubernetes Platform K8s Compute & GPU Slicing Infra Foundation for Serving 📉 Drift Audit Evidently AI Drift Detection Data & Concept Shift Monitor 📊 ML Telemetry Prometheus / Grafana Latency, Throughput, GPU vRAM 🔁 Retrain Trigger Continuous Retrain Triggers Historical Lake Pipeline
Data Ingestion Flow
Feature Pipelines
Neural Training Sweeps
Model Validation Audits
Drift Telemetry & Feedback
FREQUENTLY ASKED QUESTIONS

FAQs

We deploy models locally or within your private cloud environment (AWS VPC / Azure VNet), ensuring your proprietary training data never exits your secure perimeter.
Proof-of-concept models can be validated in 2-4 weeks, while full production-grade models integrated with automated MLOps pipelines typically span 8-12 weeks.
We set up automated data drift sensors. When incoming inference data diverges from the training set, our MLOps pipelines automatically kick off retraining, validation, and deployment stages.
GET IN TOUCH

Let's build your next intelligent application

Partner with our AI/ML engineering team to build scalable, secure, and production-grade machine learning solutions.
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"Bitsapp re-architected our core banking dashboard and shaved 60% off load times. Their team felt like an extension of ours from day one."

P

Priya Mehta

Nova FinTech

17+
Years
100+
Projects
98%
Client Retention
info@bitsapp.in
+91 9998531670
Himatnagar (S.K.), Gujarat - 383001, India