AI Integration Services
Add AI to the software you already run, through APIs and small services, without rebuilding your ERP, CRM or app.
OZRIT integrates AI into existing systems so teams get smarter features in the tools they already use. We connect models and AI services to your data and workflows with security, fallbacks and cost controls, and ship each feature behind a switch you control.
Tell us what you need
A consultant replies within one business day. No sales deck.
- 17+years building softwareFounded in Hyderabad in 2009
- 500+in-house engineersFull-time, not freelancers
- ISO/IEC 27001:2022certifiedFor information security
- 98%client retentionLong-term partnerships
AI integration, explained
You do not need a new system to get AI. You need it connected safely to the ones you trust.
AI integration means connecting AI capabilities, such as language models, document extraction, prediction or search, to existing software. A sales team sees account summaries inside the CRM; finance sees invoice fields captured inside the ERP; customers get a smarter search on your website. The software stays the same, with new abilities added around it.
Good integration is mostly careful engineering around the AI: reliable connections to your data, permissions that carry through, sensible handling when a model is slow or unavailable, caching and limits that keep costs predictable, and logging that shows what the AI saw and did. OZRIT builds those layers as small services that sit beside your systems.
Because we also build enterprise software, we can work with older systems, custom databases and unusual set-ups. We release each AI feature behind a feature flag, so you can switch it on for a few users, measure it and expand without risk to the core system.
- API and webhook integration
- ERP, CRM and database connectors
- Single sign-on and permissions
- Model gateway and routing
- Fallbacks and resilience
- Cost and usage controls
AI integration services we offer
The connections, safeguards and controls that make AI dependable inside real systems.
API and webhook integration
Connect AI services to your applications through documented APIs, events and webhooks.
ERP, CRM and database connectors
Read and write data in systems such as SAP, Dynamics, Salesforce, Zoho and custom databases.
Single sign-on and permissions
AI features follow your users, roles and access rules, so data stays where it belongs.
Model gateway and routing
One controlled entry point to several models, with routing, logging and the ability to switch providers.
Fallbacks and resilience
Timeouts, retries and graceful fallbacks, so a slow or unavailable model never stops the workflow.
Cost and usage controls
Caching, rate limits, budgets and per-team usage reports that keep AI spend predictable.
Data pipelines for AI
Clean, permissioned feeds from your systems to the AI, and results back to the right records.
Testing, monitoring and audit logs
Evaluation sets, quality monitoring and a log of every AI call for review.
How we integrate AI into existing software
Six steps that protect your core systems while the new feature proves itself.
Integrate and release
First integrated feature in 4 to 8 weeks
- 1
Review your systems
We study the applications, data, interfaces and security rules the AI will touch.
- 2
Choose the first features
We pick one or two AI features with clear value and agree how they will be measured.
- 3
Design the integration
We design the connections, permissions, fallbacks and cost limits before building.
- 4
Build the services
We build the AI services and connectors beside your system, with logging from day one.
- 5
Test and release behind a flag
We test on real cases and release to a few users first, with an easy off switch.
- 6
Measure and expand
We track quality, adoption and cost, then widen the release and add the next feature.
AI integration use cases
Common ways AI is added to existing software.
AI in your CRM
Account summaries, call and email notes, lead scoring and drafted follow-ups inside the CRM.
AI in your ERP
Invoice capture, anomaly flags, demand forecasts and plain-language explanations of numbers.
AI on your website
Smarter search, product recommendations and a support assistant connected to your catalogue.
AI in your mobile app
Voice input, summaries, recommendations and image features inside the app users already have.
AI in support tools
Suggested replies, ticket classification and knowledge search inside your helpdesk.
AI in reporting
Natural-language questions over your data, with answers and charts from your own systems.
AI integration services for your industry
The same build applies across sectors, but the data, rules and risks differ. These are the industries where we are asked for it most.
Enterprise software development
The ERP, CRM and SaaS platforms that AI features plug into, built and integrated by the same team.
IT and software development
Code and ticket assistants, test generation and AI features inside software products.
Fintech app development
Fraud signals, credit scoring, document checks and support assistants for lenders, payments and banks.
Healthcare app development
Record summaries, triage support, scheduling and personalised plans for providers and health-tech teams.
Retail and eCommerce app development
Product search, recommendations, demand forecasting and support assistants for stores and marketplaces.
Logistics app development
Route planning, ETA prediction, proof-of-delivery checks and exception alerts for fleets and supply chains.
The technology behind our AI integrations
We work with the systems you have and choose models by quality, speed, cost and privacy.
Systems we can integrate with
Packaged and custom
- SAP
- Microsoft Dynamics
- Salesforce
- Zoho
- Odoo
- Custom ERP and CRM
Models
Chosen per task, cost and privacy need
- OpenAI GPT
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral
- Hugging Face models
Integration layer
Connecting and controlling
- REST APIs
- GraphQL
- Webhooks
- Kafka
- FastAPI
- Node.js
Data and search
Your data, searchable and permissioned
- PostgreSQL + pgvector
- Pinecone
- Weaviate
- Elasticsearch
- Redis
Cloud and deployment
In your cloud account or ours
- AWS Bedrock and SageMaker
- Azure OpenAI and ML
- Google Vertex AI
- Docker
- Kubernetes
What decides the cost of AI integration
Integration is priced by how many systems the AI touches and how carefully it must be controlled.
Systems to connect
Each system adds interface work, and older systems without APIs add more.
Features to add
Each AI feature needs its own design, testing and evaluation.
Permissions and security
Role-based access, masking and audit needs add engineering effort.
Resilience requirements
Strict uptime needs more fallbacks, queues and testing.
Model and usage costs
Running cost depends on which models are used and how often.
Support and monitoring
Monitoring and updates after launch are agreed as a monthly plan.
Security and privacy in AI integration services
A security or compliance team will ask where the data goes, who can see it and how quality is checked. These are the safeguards we build into every project.
Where your data lives
Models can run in your own cloud account or on private endpoints, with provider settings that stop your data being used for training. You choose the region.
Access control
Assistants respect the permissions of the person asking. Someone who cannot open a document cannot get its content through a chat window either.
Testing before launch
We build an evaluation set from your real cases and measure accuracy, safety and cost before and after every change, not just once at launch.
Certification and ownership
OZRIT is ISO/IEC 27001:2022 certified for information security. You own the code, prompts, models you commission and your data.
All eight AI safeguardsCertifications and AI frameworks we work to
AI integration services: frequently asked questions
Straight answers on cost, timelines, data, security and ownership.
What are AI integration services?
They connect AI capabilities, such as language models, document extraction or prediction, to your existing software. The goal is to add AI features inside the tools your teams already use, without replacing those tools.
Can you add AI to our ERP or CRM?
Yes. We connect through APIs, database access or small services beside the system, and keep the permissions and records intact. This works with packaged systems that expose APIs, such as SAP, Dynamics and Salesforce, and with custom-built ones.
How much do AI integration services cost?
The cost depends on the systems involved, the features added and the security and resilience needed. A discovery sprint from $1,000 reviews your systems and ends with a scoped quote.
How long does AI integration take?
A first integrated feature usually takes 4 to 8 weeks. More features, older systems or strict security requirements take longer, and we plan the work before you commit.
Do we have to rebuild our software to use AI?
No. Most projects add AI through APIs and small services around your current software, which keeps risk low and lets you release features gradually.
What happens if the AI model is down or slow?
We design fallbacks: timeouts, retries, cached answers and a normal path that works without the AI. A model problem should slow down a feature, never stop your business process.
How do you keep AI costs under control?
We use caching, rate limits, budgets per team and cheaper models where quality allows, and we give you usage reports. We estimate running costs before the build.
Will the AI respect user permissions?
Yes. We carry user identity and roles through to the AI layer so it only sees and acts on what the user is allowed to. Sensitive fields can be masked before they reach a model.
Can you integrate with legacy systems?
Often, yes. We connect through APIs, exports, database views or bots that operate the screens, and we recommend the most reliable method for each system.
Can we switch AI providers later?
Yes. We build a gateway between your systems and the models, so a provider can be changed with limited impact. This avoids lock-in to a single vendor.
Plan your AI integration
Tell us which software you want to add AI to and what you want it to do. We will outline the integration and a safe first release.
What happens next
- 1An AI consultant reads your note and may reply with a few questions.
- 2We hold a call to understand the problem, your data and the systems involved.
- 3If AI fits, we propose a discovery sprint or a scoped pilot with clear success measures.