AI DevelopmentIntegration Services

Add AI to Your
Existing Product
in Days, Not Months

We integrate GPT-4o, Claude, Gemini, and open-source models into your existing web apps, mobile apps, and workflows — with prompt engineering, RAG pipelines, cost optimisation, and provider-agnostic architecture built in.

Providers we integrate:OpenAIAnthropicGoogleMetaMistralCohere

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ai-integration.ts

import { AIGateway } from '@kotibox/ai-sdk'

const ai = new AIGateway({

providers: ['gpt-4o', 'claude-3-5-sonnet'],

routing: 'cost-optimised',

cache: true,

}))

const response = await ai.complete({

prompt: userMessage,

context: await rag.retrieve(userMessage),

stream: true

})

// Provider: claude-3-5-sonnet (cache hit) · 0.3ms · $0.0004

73%

Cache hit rate

$0.84

Cost today

-68%

vs no-cache

Provider-agnostic

Swap GPT → Claude in 1 config line

68% cost reduction

Via caching + smart routing

10+

AI providers integrated

60%

Avg token cost reduction

2 days

Fastest feature integration

0 data

Leaves your VPC (private deployment)

What We Add to Your Product

8 AI Features — Ready to Drop Into Your Product

Each of these is a standalone AI capability we can integrate into your existing web app, mobile app, or internal tool — with a precise timeline.

3–5 days

AI Search

Replaces

CTRL+F keyword search

Delivers

Semantic understanding — finds results by meaning, not exact words

"Show me contracts with liability clauses" → finds 47 relevant contracts instantly

2–4 days

AI Writing Assistant

Replaces

Manual copywriting in your product

Delivers

In-app AI that drafts, rewrites, and improves text in your brand voice

User clicks "Improve with AI" on any text field — instantly gets 3 rewritten options

2–3 days

AI Summarisation

Replaces

Users reading entire documents

Delivers

TL;DR + key points + action items extracted from any document in seconds

Upload a 100-page legal contract → get a 5-bullet summary with risk flags in 8 seconds

3–5 days

AI Data Extraction

Replaces

Manual form filling from documents

Delivers

Structured JSON data pulled from unstructured PDFs, emails, and images

Invoice image → {vendor, amount, date, line_items} as structured data, 99.2% accuracy

5–7 days

AI Recommendations

Replaces

Rule-based "you might also like" widgets

Delivers

Semantic similarity recommendations that understand context and user intent

User reading "Node.js performance" → recommended "Redis caching strategies" not just "More Node.js articles"

3–5 days

AI Voice Input

Replaces

Typing-only interfaces

Delivers

Voice-to-text with intent understanding — user speaks, app acts

User says "create a meeting with Rahul tomorrow at 3pm" → calendar event created automatically

2–4 days

AI Image Generation

Replaces

Stock photos and manual design requests

Delivers

On-demand AI image generation from user prompts inside your product

Marketing user types "professional hero banner for SaaS product, dark theme" → 4 options in 12 seconds

5–7 days

AI Chatbot Widget

Replaces

Static FAQ pages

Delivers

Contextual AI assistant trained on your product docs and knowledge base

User on pricing page asks "which plan is right for a 50-person team?" → personalised recommendation

Provider Comparison

GPT-4o vs Claude vs Gemini vs Llama — We Help You Choose

We benchmark every provider on your actual prompts before recommending. Here is an honest breakdown of strengths, costs, and best-fit use cases.

GPT-4o

OpenAI

6 Patterns — Pick the Right Architecture for Your Use Case

How you wire AI into your product matters as much as which model you use. Here are the six patterns we implement — each with different trade-offs.

RAG Pipeline

Medium complexity3–7 days

Q&A over your documents, knowledge bases, product catalogues

How it works

User query → embed → vector search → retrieve chunks → LLM generates grounded answer

Tech Stack

Pinecone / pgvector

LangChain / LlamaIndex

OpenAI Embeddings

Any LLM

Best For

Internal knowledge bases

Customer support bots

Legal document Q&A

Product catalogue search

Timeline to Go Live

3–7 days

from kickoff to production

This pattern is included in our AI Product Layer and Enterprise packages. Can also be implemented as a standalone Feature Add-On.

Cost Optimisation

Cut AI API Costs by 50–90%

Most AI integrations burn money unnecessarily. Every integration we build includes cost optimisation by default — not as an afterthought.

Typical client result

$1,200/mo → $380/mo

After implementing all 4 techniques

Prompt caching

-90%

Model routing

-60%

Response caching

-45%

Streaming

UX boost

Prompt Caching

Up to 90% cost reduction

How it works

Cache the system prompt + context so repeated similar queries reuse the cached prefix. Anthropic charges 10% of normal for cached tokens.

Best for

Apps where system prompt is long and consistent (RAG pipelines, document Q&A)

Model Routing

50–70% cost reduction

How it works

Route simple queries (keyword lookup, basic classification) to cheap models (GPT-3.5, Haiku) and complex ones to premium models (GPT-4o, Claude Sonnet).

Best for

High-volume apps with a mix of simple and complex queries

Semantic Response Caching

30–50% cost reduction

How it works

Cache responses by semantic similarity — if a new query is 95%+ similar to a cached one, return the cached answer without an API call.

Best for

Support bots and Q&A apps where many users ask the same question in different words

Streaming + Chunking

Better UX, same cost

How it works

Stream responses token-by-token instead of waiting for the full response. Users perceive 3–4x faster responses even with the same backend latency.

Best for

Any chat or writing assistant UI — dramatically improves perceived performance

Architecture

Provider-Agnostic by Design — Swap Models in One Line

AI models improve every 6 months. We build an abstraction layer so you can upgrade providers without touching application code — your product evolves as AI evolves.

Audit Current Stack

We review your existing codebase, identify all AI touch-points, assess provider lock-in, and document token usage patterns.

Output

Dependency map + risk assessment

Provider Selection

We benchmark GPT-4o, Claude, and Gemini on your actual use case prompts — measuring accuracy, cost, and latency before recommending.

Output

Benchmark report + recommendation

Abstraction Layer

We build a provider-agnostic AI gateway layer so you can swap models without touching application code — future-proofing your integration.

Output

AI gateway with unified API

Optimise & Monitor

Implement caching, routing, and streaming. Set up cost dashboards and quality monitoring with automated alerts.

Output

Cost dashboard + alert system

Packages

AI Integration Packages

From a single AI feature to a full enterprise AI platform — three scopes, one standard of engineering quality.

Feature Add-On

1–2 AI features

Live in 1–2 weeks

What's Included

1–2 AI features integrated (see feature list)

Provider selection & prompt engineering

API integration into your codebase

Basic error handling & fallbacks

Cost tracking setup

2-week post-launch support

Not included

RAG pipeline

Fine-tuning

Semantic caching

Multi-model routing

Adding a specific AI capability to an existing product

Tell Us What You're Building.
We'll Tell You How to Add AI.

A free 45-minute technical call where we review your stack, identify the right integration pattern, pick the best provider for your use case, and give you a cost estimate.

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