Managed AI & Support for Indian Enterprises: Run AI in Production
A pilot that dazzled the board can quietly fail in production. Models drift as data shifts, token and GPU bills climb, and unchecked outputs invite compliance risk. Opsio operates your AI from our ISO 27001-certified Bangalore centre, with 24/7 follow-the-sun support, drift and quality evaluation, INR cost optimization, retraining, and analytics, all under firm SLAs.
Trusted by 100+ organisations across 6 countries
24/7
Bangalore + Sweden NOC
<15min
Critical incident response target
99.9%
Operational uptime SLA
50+
Cloud & AI engineers
What's Included
Managed AI & Support spans the entire operational life of production AI, delivered as one accountable service rather than a toolkit you assemble yourself. We bring together LLMOps and MLOps engineering, round-the-clock monitoring, structured evaluation, rupee-focused cost control, and analytics, all under SLAs. Your stack may run on Amazon Bedrock, Azure OpenAI, Google Vertex AI, open-weight models on dedicated GPUs, or a blend, and the operating logic stays constant: make behaviour visible, make regressions catchable, make spend predictable, and make improvement continuous. The six capabilities below are the foundations of the service. Each is delivered by named engineers working a follow-the-sun rhythm from our Bangalore centre and Sweden, instrumented with proven tooling, and reported back to you openly, so you always know how your AI performs and what we are doing to keep it sharp.
24/7 AI Monitoring & Support
Our Bangalore and Sweden NOC monitors your AI services every hour, alerting on latency, errors, quality drops, and cost spikes. Critical incidents draw a sub-15-minute response with clear escalation and on-call engineers familiar with your environment.
Model Drift & Quality Evaluation
We score live outputs continuously for accuracy, groundedness, and distribution shift using automated evaluation suites and LLM-as-judge techniques. Drift surfaces as a measurable signal, prompting review or retraining before customers or regulators notice.
LLMOps & MLOps Engineering
We run the operational pipeline end to end: versioned prompts and models, AI CI/CD, registries, automated regression gates, and reproducible deployments. Every change is tested and traceable, keeping audit trails intact for compliance review.
Cost Optimization (Token & GPU)
We trace token and GPU spend to the request level and cut it via right-sizing, caching, prompt compression, batching, and tiered routing, favouring India-region endpoints where sensible. Rupee unit economics become a metric we actively manage.
Retraining & Lifecycle Management
We run scheduled and trigger-based retraining, manage data versioning and labelling, and validate each new model against your evaluation suite before promotion. Models stay current and compliant without manual scrambles or unplanned downtime.
AI Analytics & Reporting
We convert operational telemetry into dashboards and reports covering model performance, usage, rupee cost trends, and business outcomes. Leadership sees AI's real contribution while engineers get the signals to prioritise the next improvement.
Opsio's focus on security in the architecture setup is crucial for us. By blending innovation, agility, and a stable managed cloud service, they provided us with the foundation we needed to further develop our business. We are grateful for our IT partner, Opsio.

Jenny Boman
CIO · Opus Bilprovning
Production AI for Indian enterprises, operated and governed
Indian enterprises have moved fast from AI curiosity to AI deployment. BFSI players, global capability centres, and ITeS firms now have models making real decisions and answering real customers. The challenge has shifted accordingly: the hard part is no longer building a model, it is keeping it dependable once it carries production load. Opsio's Managed AI & Support is built for exactly this stage. We take operational ownership of your deployed AI, instrument it for visibility, and run it against measurable service levels from our ISO 27001-certified delivery centre in Bangalore. That turns a promising pilot into a capability your organisation can stake business decisions on, without your own team firefighting at odd hours. Operating AI is unlike operating ordinary software, and that difference trips up many in-house teams. The code can sit untouched while the model's accuracy slips, because the data it learned from no longer matches the data it now sees. A credit model meets a new customer segment; a vernacular support assistant meets an unfamiliar phrase; a document system meets a corpus that has doubled. None of these raise an error. Opsio handles this by treating the model's own behaviour as something to be watched, sitting alongside latency and uptime. We monitor accuracy, groundedness, and output patterns as first-class signals, so quality loss shows up on a dashboard, not in a regulator's query or a customer escalation.
Cost discipline matters acutely in the Indian market, where AI economics are scrutinised closely against business value. Token consumption and GPU hours grow with adoption, and waste hides easily: bloated prompts, oversized context, needless retries, and premium models doing work a cheaper tier could handle. Left alone, the rupee cost of AI can balloon without any gain for users. Opsio profiles where your AI budget genuinely goes and engineers it down through model right-sizing, caching, prompt compression, batching, and intelligent routing. We manage unit economics as an operational metric, choosing India-region endpoints where they help with both latency and data residency, so your AI stays commercially justifiable as it scales across the organisation.
Governance is not optional for Indian enterprises, and it cannot be retrofitted. The DPDP Act 2023, RBI expectations for regulated entities, and CERT-In directives all shape how AI must be operated, logged, and secured. Opsio bakes these concerns into the operating model: guardrails and output filtering in the request path, continuous sampling and scoring of live responses, automated evaluation gates before any prompt or model change ships, and audit-ready logging from our ISO 27001-certified environment. Data residency and access control are handled deliberately, not assumed. This gives risk, compliance, and security leaders the evidence they need to defend AI use to boards and regulators alike, and lets the business adopt AI with confidence rather than caution.
Operating AI well also generates insight that too many teams discard. Every request, evaluation, and cost data point describes how your AI and your business are performing. Opsio converts that telemetry into AI analytics: dashboards and reports on model performance, usage, rupee cost trends, and business outcomes, giving leadership a clear line of sight into AI's contribution and where to invest next. Managed AI & Support is therefore far more than keeping systems alive. It is a continuous-improvement engine in which operation feeds measurement, measurement drives optimization, and your AI grows steadily more reliable, more compliant, and more valuable to the enterprise over time. Featured reading from our knowledge base: Managed DevOps Services: Outsourcing DevOps Done Right for Indian Enterprises, Machine Learning Cloud: Build, Deploy & Scale ML in Production for Indian Enterprises, and Azure Managed Services: Features, Benefits & Real-World Use Cases for Indian Enterprises. Related Opsio services: AI Development & Integration for Indian Enterprises, AI Solutions & Strategy for Indian Enterprises: Roadmap to ROI, MLOps Consulting & Implementation India, and AI Visual Inspection for Indian Manufacturing.
How Opsio Compares
| Capability | In-House Ad Hoc | Generic Cloud Support | Opsio Managed AI |
|---|---|---|---|
| AI quality & drift monitoring | Manual, sporadic | Infrastructure only | Continuous, automated |
| 24/7 coverage (India time) | Business hours | Offshore ticket queue | Bangalore + Sweden, real engineers |
| DPDP / RBI / CERT-In awareness | Inconsistent | Not addressed | Built into operating model |
| Token & GPU cost (INR) optimization | Reactive | Not included | Actively managed metric |
| Retraining & lifecycle | When someone remembers | Out of scope | Scheduled & trigger-based |
| AI analytics & reporting | Ad hoc spreadsheets | Generic dashboards | Model, cost & business insight |
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What You Get
Pricing & Investment Tiers
Transparent pricing. No hidden fees. Scope-based quotes.
Essential
from approx. INR 2.5 lakh/month
24/7 monitoring, incident response, and support for a small number of production models. Illustrative; varies by scope.
Professional
approx. INR 7-13 lakh/month
Adds drift and quality evaluation, active INR cost optimization, guardrails, and monthly AI analytics across multiple models. Illustrative; varies by scope.
Enterprise
custom retainer
Full LLMOps/MLOps operation, strict SLAs, dedicated on-call engineers, retraining pipelines, and compliance-grade reporting at scale. Illustrative; varies by scope.
Transparent pricing. No hidden fees. Scope-based quotes.
Questions about pricing? Let's discuss your specific requirements.
Managed AI & Support for Indian Enterprises: Run AI in Production
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