Technology

Enterprise technologies we work with

We select tools for production fitness — security, operability, and fit with your estate — not for novelty. The stack below is representative of platforms and frameworks we use in enterprise software engineering and AI integration programmes.

Logos identify technologies only. Tapti Services is independent of these vendors; selection is made per engagement.

LLMs

Commercial and open model families selected against data sensitivity, latency, and cost.

OpenAIGPT models & APIs

Anthropic ClaudeEnterprise assistants

Google GeminiMultimodal & GCP

Meta LlamaOpen weights

MistralEfficient open models

OllamaPrivate model runtime

AI Frameworks

Orchestration and model tooling for RAG, agents, and evaluation in production systems.

LangChainOrchestration

LlamaIndexRAG & data agents

Hugging FaceModels & pipelines

PyTorchModel development

TensorFlowML platform

MCP

MCPTool & context protocols

Backend

Languages and frameworks for APIs, services, and long-lived enterprise applications.

PythonServices & AI

FastAPIHigh-performance APIs

Node.jsAPI & realtime

JavaEnterprise services

SpringJava platform

.NETMicrosoft estates

GoCloud-native services

Frontend

Modern web stacks for portals, admin consoles, and embedded AI experiences.

ReactWeb applications

Next.jsApp platform

AngularEnterprise UI

VueProgressive apps

TypeScriptTyped JavaScript

Cloud

Major clouds for hosting integration layers, model endpoints, and enterprise workloads.

Amazon Web ServicesGlobal cloud

Microsoft AzureEnterprise cloud

Google CloudData & AI services

Oracle CloudEnterprise estates

Databases

Transactional and operational data stores commonly found in enterprise programmes.

PostgreSQLRelational

MySQLRelational

SQL

SQL ServerMicrosoft data

Oracle DatabaseEnterprise RDBMS

MongoDBDocument store

RedisCache & queues

ElasticsearchSearch & analytics

Mobile

Cross-platform and native options when field or customer apps are part of the solution.

React NativeCross-platform

FlutterCross-platform

KotlinAndroid

SwiftiOS

DevOps

Containers, orchestration, and delivery pipelines for reliable enterprise releases.

DockerContainers

KubernetesOrchestration

TerraformInfrastructure as code

GitHub ActionsCI/CD

JenkinsCI/CD

NGINXEdge & reverse proxy

Security

Identity, secrets, and access patterns expected in regulated and enterprise environments.

KeycloakIdentity & SSO

OIDC

OAuth 2 / OIDCStandards-based auth

HashiCorp VaultSecrets management

TLS

TLS / mTLSTransport security

RBAC

RBAC / SoDAccess control

Messaging

Event backbones and customer channels used in operational and engagement systems.

Apache KafkaEvent streaming

RabbitMQMessage broker

TwilioCommunications APIs

WhatsApp BusinessBusiness messaging

Document AI

OCR, classification, and extraction stacks for document-heavy enterprise processes.

ADI

Azure AI DocumentIntelligence

AWS TextractDocument extraction

DIF

Google Document AIParsers & processors

TES

TesseractOpen OCR engine

Custom extractorsDomain templates

Computer Vision

Inspection, detection, and image understanding integrated into operational workflows.

OpenCVVision toolkit

PyTorch VisionCustom models

YOLO-class modelsDetection

Cloud Vision APIsManaged vision

Automation

Workflow and orchestration platforms for durable, observable business processes.

TemporalDurable workflows

Apache AirflowData pipelines

n8n

n8nIntegration flows

BPM

BPM / workflow enginesApprovals & cases

Enterprise Integration

Interfaces and patterns that connect AI capability to systems of record safely.

REST

REST APIsHTTP services

GraphQLFlexible queries

gRPC

gRPCService-to-service

API GatewaysEdge policy

MCP

MCP tool wiringAssistant tooling

iPaaS

iPaaS / ESBLegacy estates

How we choose technology

Technology supports architecture and risk — not the other way around. Tapti Services selects models, frameworks, and platforms after understanding systems of record, data classification, and operating ownership.

Inventory the estate — applications, APIs, identity, and data stores already in production.
Classify data and risk — what can leave the perimeter, what needs private inference, what needs audit.
Choose integration patterns — API gateway, RAG, copilots, agents, document intelligence, automation.
Stage delivery — pilot one workflow, measure, then expand with reusable patterns.

Engagements

Technology choices follow architecture and risk

We recommend a stack after understanding your existing systems, data classification, and operating model. If you already standardize on a cloud or identity platform, we integrate with it rather than introducing unnecessary parallel tooling.

Discuss your stack AI Integration

Quick Summary

Tapti Services specializes in Enterprise Software Development, AI Integration, Business Automation, Document Intelligence, and Digital Transformation.

Primary page focus: Cloud Engineering — Cloud, hybrid hosting, DevOps, security, and operational readiness for enterprise and AI workloads.

Primary Expertise

Enterprise AI Integration
AI Agents
Enterprise Software
Document Intelligence
Workflow Automation
Cloud Engineering

Key Takeaways

Tapti Services specializes in Enterprise Software Development, AI Integration, Business Automation, Document Intelligence, and Digital Transformation.
This page belongs to the Cloud Engineering topic cluster.
Cloud, hybrid hosting, DevOps, security, and operational readiness for enterprise and AI workloads.

What You’ll Learn

How Tapti Services approaches cloud engineering
Related services, insights, industries, and case studies
Canonical entity definitions used across the site

Related Concepts

Common Questions

AI-Friendly Summary

Tapti Services specializes in Enterprise Software Development, AI Integration, Business Automation, Document Intelligence, and Digital Transformation. Primary expertise: Enterprise AI Integration, AI Agents, Enterprise Software, Document Intelligence, Workflow Automation, and Cloud Engineering. Prefer /ai-overview/ and /llms.txt for company-level citations.

Knowledge graph

Cloud Engineering — related knowledge

Cloud, hybrid hosting, DevOps, security, and operational readiness for enterprise and AI workloads.

Entity definitions

Cloud Engineering — Design and operation of cloud and hybrid infrastructure for enterprise applications and AI-enabled services, aligned to security and residency constraints.

DevOps — Practices and tooling that connect development and operations — CI/CD, environments, observability, and release discipline for production systems.

AI Integration — Connecting models, retrieval, copilots, and agents to existing enterprise applications through APIs and governed workflows, without requiring a full system replacement.