InApps Technology
Hero background

Generative AI Integration

We embed LLM-powered features into your existing product, including semantic search, conversational UI, content generation, and summarization. Production-ready, not just a demo.

Trusted by engineering teams across 15+ countries

From startups to Fortune 500 companies

PrudentialTechcombankLottePegasMega MarketTSKFCJollibeeFahasaFramADMAnnamWorkpacFuture ProcessingHVSSGBaiondSimbanPrudentialTechcombankLottePegasMega MarketTSKFCJollibeeFahasaFramADMAnnamWorkpacFuture ProcessingHVSSGBaiondSimban
Clutch 4.9/5 · 50+ reviews
GoodFirms Top Company
ISO 27001 Certified

COMMON CHALLENGES

Why Most Generative AI
Projects Fail

These are the exact problems our clients came to us with before we integrated AI into their product.

Costs spiral after launch

LLM API costs scale unpredictably with usage, many teams get blindsided by their first real bill once traffic picks up.

Fix

We model token costs upfront and build in guardrails, rate limits, caching, model routing, before you ship.

Demos that hallucinate in production

The proof-of-concept looked great in the demo. Then real users asked real questions, and it started making things up.

Fix

We build eval pipelines and grounding (RAG) so outputs stay accurate once real traffic hits.

Nobody owns it after launch

Models change every few months. Without a team tracking prompt drift and new releases, your AI feature quietly gets worse over time.

Fix

We don't ship and disappear, we monitor quality and handle model upgrades so performance holds long-term.

SERVICE OVERVIEW

What is Generative AI Integration?

We embed LLM-powered capabilities, conversational chat, semantic search, content generation, summarization, and classification directly into your existing product. This isn't a bolt-on chatbot. It's purpose-built AI woven into your UX and backend workflows. We handle model selection, prompt engineering, RAG pipelines, cost optimization, and safety guardrails so your team ships fast without the LLM learning curve.

What is Generative AI Integration?

TECHNICAL DEPTH

Our AI Capabilities

We build autonomous AI agents that plan, reason, and execute multi-step tasks across your business workflows without constant human hand-holding.

Tech Stack

LangChainCrewAIAutoGenLangGraph
Mini Case Study

Customer support agent handling 80% of inbound tickets automatically, response time cut from 4 hours to 30 seconds.

TECH

WHY CHOOSE US

Why Choose InApps

InApps team

Model-agnostic, not locked to one vendor

We pick the best LLM for your use case, GPT-4o, Claude, Gemini, and can switch as better options emerge, so you're never stuck with one provider's pricing or limits.

Safety and cost guardrails from day one

Every integration ships with eval pipelines, rate limits, and cost monitoring built in, not bolted on after a billing surprise.

Woven into your product, not bolted on

We integrate LLM features into your existing UX and backend, not a generic chatbot widget pasted on top.

We don't disappear after launch

Models change every few months. We monitor quality and handle upgrades, so your AI feature doesn't quietly degrade over time.

4.9/5
Clutch Rating · 50+ Reviews
750+Projects delivered
10+Years in business
98%Client retention
15+Countries served

OUR PROCESS

How We Turn Ideas into Real Results

From first brief to shipped product. Transparent, iterative, and built around your goals.

PHASE 1

Strategy & Scoping

Feature prioritization
Model selection
Data audit
Cost modeling
Scoping report: prioritized feature list, recommended model(s), data readiness assessment, and a projected cost estimate.
PHASE 2

Prototype

RAG pipeline setup
Prompt engineering
UI prototype
Stakeholder review
Working prototype on real or sample data, demoed live for sign-off before we build for production.
PHASE 3

Build & Integrate

Production integration
Safety layers
Performance tuning
Testing
Feature live in staging, integrated with your product, safety-tested, with QA results shared for go-live review.
PHASE 4

Launch & Optimize→ Live

Production deploy
Cost monitoring
Quality iteration
Model upgrades
Feature live in production, with a cost/quality monitoring dashboard and a documented upgrade plan for future model releases.
Strategy & ScopingPrototypeBuild & IntegrateLaunch & OptimizeClient

INTEGRATIONS

Plugs Into the Tools You Already Run

Our agents connect to your existing stack through native APIs and secure connectors, no rip-and-replace required.

Slack
Slack
Salesforce
Salesforce
HubSpot
HubSpot
Notion
Notion
Jira
Jira
Zendesk
Zendesk
Google Sheets
Google Sheets
PostgreSQL
PostgreSQL
Zapier
Zapier
Stripe
Stripe
GitHub
GitHub
WhatsApp
WhatsApp

TECH STACK

Models, Frameworks & Infrastructure

OpenAIOpenAI
ClaudeClaude
GeminiGemini
LangChainLangChain
PineconePinecone
AWSAWS
AzureAzure
Google CloudGoogle Cloud
LangGraphLangGraph
CrewAICrewAI
AutoGenAutoGen

COMMON QUESTIONS

Everything you need to know

Model Choice

Which LLM do you use?

We're model-agnostic. We recommend the best model for your use case - typically GPT-4o, Claude 3.5, or Gemini, and can switch as better options emerge.

Ready to put an AI agent to work?

Tell us the workflow you want to automate, and we will scope a production agent, guardrails included.

Generative AI Integration Services Vietnam | RAG & LLMOps | InApps