AI that runs in production, not just in demos
AI Services
We help companies put AI to work where it pays back fastest: fewer outages, faster support and smarter automation. Built and run by the same engineers who keep 10,000+ servers online 24/7.
24/7
Operations team
10,000+
Servers managed
300+
Engineers in Kochi
Since 2012
Running production infrastructure
Everyone is talking about AI. Few businesses are getting results.
Most AI projects stall between the pilot and production. The model works in a demo, but nobody owns the data pipelines, the infrastructure, the security or the 3 AM incident when it breaks. VIPoint closes that gap by combining AI engineering with the 24/7 operations discipline we have built over more than a decade.
Our AI services
1. AIOps: AI for IT operations
Use AI to keep your infrastructure healthy and your team focused.
- Anomaly detection on servers, applications and logs, so problems are caught before customers notice
- Alert noise reduction and correlation: fewer, smarter alerts
- AI-assisted root-cause analysis and incident summaries
- Automated remediation runbooks for common issues, with human approval where needed
- Capacity forecasting and cost insights
Related: AIOps for server management · 24/7 server management
2. AI agents and chatbots for support
Answer customers instantly and help your agents work faster.
- AI support agents trained on your knowledge base, tickets and documentation
- Smooth handover to human agents with full context
- Agent copilots that draft replies, summarise tickets and suggest fixes
- Integrations with WHMCS, Zendesk, Freshdesk, HubSpot, Slack, Teams and WhatsApp
Related: Live chat support in 2026 · Helpdesk support
3. AI infrastructure and MLOps
Run AI on infrastructure you control, securely and cost-effectively.
- Private LLM hosting for companies that can’t send data to public AI services
- GPU server setup and management, on-premises or in AWS and Azure
- Vector databases, model serving, Kubernetes and autoscaling
- Monitoring of model performance, latency and cost
- MLOps pipelines for versioning, testing, deployment and retraining
4. AI engineering and integration
Add AI to your products and workflows.
- LLM integration into apps, portals and internal tools
- Workflow automation with AI agents for documents, emails, reports and data entry
- Custom machine learning for forecasting, classification and computer vision
- Data engineering to get your data AI-ready
- Proof of concept in 4–8 weeks, then production rollout
5. AI security and governance
Use AI without creating new risks.
- Security reviews of AI applications: prompt injection, data leakage and access control
- AI usage policies and approved-tool setups to stop “shadow AI”
- Logging, audit trails and guardrails for AI agents
- Technical support for data protection obligations such as GDPR and India’s DPDP Act, and alignment with frameworks like ISO/IEC 42001
Need AI engineers rather than a project?
Hire dedicated AI, data and MLOps engineers who work only for you, through our dedicated engineers model.
Where AI pays back first
| Use case | Typical benefit | Who it suits |
|---|---|---|
| AI support agent on your knowledge base | Instant answers to common questions, 24/7 | Hosting, SaaS, e-commerce |
| AIOps alert correlation | Less alert noise, faster incident response | Any team running servers or cloud |
| Ticket summarisation and reply drafting | Faster resolution, consistent quality | Helpdesks and MSPs |
| Document and email automation | Hours saved on repetitive admin | Operations, finance, HR |
| Private LLM for internal knowledge | AI answers without sending data outside | Regulated or IP-sensitive firms |
How we work
| Step | What happens |
|---|---|
| 1. Free AI opportunity workshop (1 hour) | We map your processes and data, and shortlist 2–3 high-value use cases |
| 2. Pilot (4–8 weeks) | A working proof of concept on real data, with clear success measures |
| 3. Production | Secure deployment, integration, monitoring and guardrails |
| 4. Run and improve | 24/7 operations, cost control, retraining and new use cases |
Why VIPoint for AI
- Operations DNA: we have run production infrastructure 24/7 since 2012. AI systems need the same discipline.
- Full stack: data, models, infrastructure, security and support from one team.
- Practical, not hype: we start with use cases that pay back, then scale.
- Flexible models: projects, managed AI operations or dedicated AI engineers.
Technologies
OpenAI, Anthropic, Google Gemini and Azure OpenAI APIs; open models such as Llama, Mistral and Qwen; LangChain and LlamaIndex; vector databases such as pgvector, Qdrant and Chroma; vLLM and Ollama for model serving; Python, PyTorch and scikit-learn; Kubernetes, Docker and Terraform; Prometheus, Grafana and OpenTelemetry; AWS Bedrock and SageMaker; Azure AI Foundry.
Frequently Asked Questions
Do we need a lot of data to start?
No. Many high-value use cases, such as support agents and document automation, use your existing knowledge base, tickets and documents.
Will our data be sent to public AI providers?
Only if you choose to. We can use enterprise APIs with data protection terms, or run open models privately on your own servers or cloud account.
How long until we see results?
A focused pilot usually takes 4–8 weeks. Production rollout depends on integrations and security requirements.
How much does it cost?
The workshop is free. Pilots are fixed-price, and ongoing AI operations are a monthly fee agreed upfront.
Can AI replace our support or operations team?
AI handles repetitive work and speeds people up. It works best alongside experienced engineers, which is how we deliver it.
Find out where AI can save you time and money
Book a free one-hour AI opportunity workshop with our engineers. You’ll leave with 2–3 practical use cases and a rough cost estimate.