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AI Integration Services

AI Integration Services That Plug Into the Systems You Already Run

We connect the right AI model to your CRM, ERP, help desk, data and product, with the permissions, guardrails and monitoring that let it run in production. No rebuild, no vendor lock-in.

  • Any modelOpenAI, Claude, Gemini, Llama and Mistral
  • 1 to 2 weeksto a first version in your environment
  • From $22/hrsenior AI engineers, your US hours

Rated 4.9 on Clutch from 55 verified reviews. Building software since 2015.

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The short answer

What Is AI Integration?

AI integration is connecting AI models to the software your business already runs, so AI can read your data and take action inside your existing workflows. It covers choosing the model, connecting it to your systems, keeping data permissions intact, and measuring and monitoring the result in production.

It is different from building a new AI product. Integration is usually the faster path to a return, because your data, users and processes already exist. Depending on the job we use LLM API integration, MCP, retrieval over your documents or workflow automation.

  • ConnectThe model reads and writes your real systems through scoped, audited access
  • ControlPermissions, redaction, evaluation and human review before it affects customers
  • Keep it runningCaching, fallbacks and monitoring so it survives traffic spikes and provider outages
Where AI plugs in

Systems We Integrate AI Into

The best first integration is usually the system where your team already spends its day reading, typing and searching. These are the ones we connect most.

Customer support

Zendesk, Freshdesk, Intercom, email

  • Draft replies from your help articles and past tickets
  • Classify, prioritize and route incoming requests
  • Summarize long threads for the next agent

Sales and CRM

Salesforce, HubSpot, Pipedrive

  • Summarize accounts and call notes into the CRM
  • Score and enrich inbound leads
  • Draft follow-ups for a rep to approve

Finance and ERP

NetSuite, SAP, QuickBooks, Xero

  • Extract data from invoices and contracts
  • Match and reconcile line items, flag exceptions
  • Answer questions over ledgers and reports

Knowledge and documents

SharePoint, Confluence, Drive, Notion

  • Search across wikis and drives in plain English
  • Cited answers that respect who can see what
  • Keep answers current as documents change

Your own product

Web apps, mobile apps, SaaS platforms

  • In-app assistants that know your product
  • Smart search and recommendations
  • Content and summary features behind a feature flag

Data and operations

Snowflake, BigQuery, Postgres, internal APIs

  • Classify and enrich records at scale
  • Natural-language questions over your data
  • Automate approvals, routing and data entry
Our Process

How We Deliver Your AI Integration Project

01

Discovery & Strategy

AI agents analyze requirements and market data to build a precise blueprint.

1-3 Days
02

Architecture & Design

AI-first system design with UI/UX prototypes and technical planning.

3-5 Days
03

AI Sprint Build

6 AI specialists work in parallel at 10-20X velocity with continuous integration.

1-4 Weeks
04

QA & Launch

Automated testing validates every component. Zero-downtime deployment from day one.

2-3 Days
05

Iterate & Scale

AI agents monitor, optimize, and ship improvements. Evolve faster than competition.

Ongoing
Built to be trusted

Risks and the Control for Each

AI integrations fail in predictable ways. Every build ships with a specific control for each of these, not an optional add-on.

Data leaving your control

Sensitive customer or financial data gets sent to a model it should never see.

How we handle itThe model gets only the fields a task needs. Sensitive values are redacted or tokenized, and enterprise terms or private deployments are used where policy requires.

Wrong access

The assistant shows someone a record they are not allowed to see.

How we handle itAccess follows your existing roles. Retrieval filters by user permission before the model sees anything, and every call is logged.

Confident wrong answers

The model states something false and a person acts on it.

How we handle itWe build an evaluation set from your real cases, ground answers in approved sources with citations, and route low-confidence cases to a person.

Surprise bills

Usage spikes and the model bill arrives as a shock.

How we handle itCaching, model routing, per-feature budgets and alerts keep cost visible and capped from the first release.

Provider outages and changes

The model provider has an outage or retires the model you depend on.

How we handle itA model-neutral layer with fallbacks means you can switch provider or model without rewriting your application.

Silent quality drift

It works at launch, then quietly gets worse as data and prompts change.

How we handle itScheduled evaluation runs and monitoring catch regressions, and we hand over the dashboards and runbooks.

Cost and timeline

What Drives the Cost of AI Integration

We quote after a short scoping call and a fixed-scope first sprint, so you see a working version before committing to the full build.

Five things that set the price

No two integrations cost the same. These are the levers.

  • Number of systems: one CRM is simple, five systems with different APIs is not
  • State of the APIs: clean documented APIs are fast, legacy systems need an adapter layer
  • Data readiness: messy or scattered data needs cleanup before AI can use it
  • Quality bar: a drafting tool and an automated decision have very different testing needs
  • Security and compliance: regulated data adds redaction, audit and hosting requirements

How a typical engagement runs

Senior AI engineers from $22/hr, working your US hours.

  1. Scoping callFree. We agree the workflow, the systems involved and how success is measured.
  2. First sprintFixed scope. A working version in your environment, usually in 1 to 2 weeks.
  3. Production buildHardening, evaluation, monitoring and rollout, typically 3 to 8 more weeks depending on scope.
  4. OngoingOptional support and a dedicated engineer to expand to the next workflow.
Not sure where AI fits in your stack?Tell us the systems you run and we will point to the first integration worth doing, even if it is not with us.
Get a free scoping call
Tech Stack

The Stack We Use for AI Integration

Model-neutral by design: we pick tools for your systems, not the other way round.

Models

OpenAI GPT Anthropic Claude Google Gemini Meta Llama Mistral

Integration and orchestration

Model Context Protocol (MCP) LangChain LlamaIndex REST and GraphQL APIs Webhooks and queues

Data and retrieval

PostgreSQL and pgvector Pinecone Snowflake and BigQuery

Languages and cloud

Python TypeScript AWS Azure Google Cloud Docker

Why Clients Choose Groovy Web for AI Integration

Senior AI engineers

The people who scope your integration are the people who build it. No juniors learning on your budget.

Works in your stack

We integrate with the CRM, ERP, help desk and databases you already use. Nothing has to be replaced to get value.

Model-neutral

The integration layer lets you switch models as prices and quality change, with no rewrite and no vendor lock-in.

Measured, not demoed

We build an evaluation set from your real cases before launch and track it after, so quality shows up in numbers.

You own everything

Code, prompts, pipelines and dashboards are yours, with documentation and a clean handover.

Your working hours

Four hours of daily overlap with US Eastern, with live standups and a one-week risk-free trial.

FAQ

AI Integration Services FAQ

AI integration is connecting AI models to the software your business already runs, such as your CRM, ERP, help desk or product, so AI can read your data and act inside your existing workflows. It includes choosing the model, connecting it securely, keeping permissions intact and monitoring quality in production.
Cost depends on the number of systems involved, how clean their APIs are, how ready your data is, the quality bar the output must meet and any security or compliance requirements. We quote after a free scoping call and a fixed-scope first sprint, so you see a working version before committing to the full build. Our senior AI engineers start from $22/hr.
A first working version inside your real environment usually takes 1 to 2 weeks. Hardening it for production, with error handling, caching, evaluation, monitoring and access controls, typically adds 3 to 8 weeks depending on how many systems are involved.
You do not have to use OpenAI. We integrate OpenAI, Anthropic Claude, Google Gemini and open-weight models such as Llama and Mistral, and we recommend one based on accuracy on your task, latency, cost and data-residency needs. The integration is built so the model can be swapped later without rewriting your application.
Usually yes. We add a thin integration layer in front of the legacy system, such as a read-only database replica, a message queue, scheduled exports or a purpose-built API wrapper, so AI features can read and write data safely without changing the core system. If the legacy system is the real bottleneck, we will say so and scope a modernization step first.
The model receives only the fields a task needs, sensitive values are redacted or tokenized before the call, and enterprise API terms or private deployments are used where required. Access follows your existing roles and permissions, every model call is logged, and models can run inside your own cloud account when policy demands it.
AI integration adds AI to software you already run. A new AI product is built from scratch. Integration is usually faster and cheaper because the data, users and workflows already exist, and it is where most companies see their first measurable return.
Book a free scoping call through the quote form. A senior AI engineer replies within one business day, agrees the first workflow and success metric with you, and proposes a fixed-scope first sprint.
AI-First Engineering

Production-Grade AI, Built by Senior Engineers

AI tools and offshore teams get you 80% of the way. Our senior engineers own the last 20%: security, architecture and production hardening, working your US hours.

Plan
Product strategy, requirements, roadmap
Build
Design, frontend, backend, APIs
Deploy
QA, CI/CD, monitoring, launch
Grow
Analytics, optimization, scale
Full-Stack AI Development
Frontend, backend, APIs, databases — all AI-augmented
AI Agent Orchestration
6+ specialized AI agents working in parallel
10-20X Velocity
Ship in weeks what takes others months
Starting price $22/hr
Hire AI-First Engineer

Flexible engagement models — monthly, quarterly, or annual commitments

Are you looking for an AI integration engineer?

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Why Groovy?

500+

Project Delivered

250+

Happy Clients

99%

Client Satisfaction Rate

50%

Recurring Clients

150%

Average Company Growth

40+

5 Star Ratings on Clutch.co

100+

In-House Talent
AI Integration Developer
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