AI Solutions & Services

AI Solutions & Services that work on real data, in real workflows

O Clock Software, headquartered in Chennai, India, designs, builds and operates AI systems for businesses: LLM applications, retrieval-augmented assistants, agents, machine learning models and computer vision. Every engagement starts with the problem and the data, and ends with something measured in production rather than a demo.

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  • 2009Founded in Chennai
  • 1,000+Projects delivered
  • 12+Countries served
  • 100+Engineers in-house
  • 4.6★Google rating · 59 reviews

Recognized & Reviewed On

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Our services

14 AI & Intelligent Solutions services

We build AI that has to work on real data, inside real workflows. That covers LLM and generative AI applications, retrieval-augmented assistants, agents that complete multi-step tasks, classic machine learning and computer vision, and the MLOps that keeps models accurate after launch.

Choosing the approach

Which AI approach fits your problem?

Most AI projects that disappoint picked the wrong technique, not the wrong model. This is how we decide, and we will tell you if the simplest option is enough.

Approach Use it when Avoid it when Typical example
Prompted LLM The task is language-based and general knowledge is enough Answers must come from your private data Drafting replies, summarising tickets
RAG (retrieval-augmented generation) Answers must come from your documents, with sources Data changes faster than it can be indexed, or is mostly numeric Policy and product knowledge assistants
Fine-tuned model You need a consistent style, format or domain vocabulary at scale You have fewer than a few hundred good examples Structured extraction in a fixed format
AI agent A task spans several systems and steps, with clear rules Mistakes are high-impact and steps cannot be approved by a person Triage, then create and route a support case
Classic machine learning You have labelled historical data and a numeric target There is no history to learn from Demand forecasting, churn and risk scores
Computer vision The signal is in images or video Lighting and camera setup cannot be controlled Damage assessment, counting, quality inspection

How we deliver

How we deliver AI & Intelligent Solutions

Five steps, adapted to this kind of work, with working software or a tested prototype shown at every stage.

  1. 01

    Frame

    Define the decision or task, the users, and how success will be measured.

  2. 02

    Data check

    Audit the data you have, its quality, access rules and gaps.

  3. 03

    Prototype & evaluate

    Build a working slice and score it against a test set, not impressions.

  4. 04

    Productionise

    Integrate, secure, add guardrails, human review and logging.

  5. 05

    Operate

    Monitor accuracy, drift and usage; retrain and improve on a schedule.

Technology

Technologies we use

Chosen per project for fit, maintainability and your team's skills, not out of habit.

Models

  • OpenAI GPT
  • Anthropic Claude
  • Google Gemini
  • Meta Llama
  • Mistral

Frameworks

  • LangChain
  • LlamaIndex
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Hugging Face

Vector & data

  • pgvector
  • Pinecone
  • Qdrant
  • Elasticsearch
  • PostgreSQL

MLOps & cloud

  • MLflow
  • Docker
  • Kubernetes
  • AWS SageMaker
  • Azure AI
  • Google Vertex AI

Straight answers

When this is the right call, and when it is not

We would rather recommend less than sell you more. Here is how we judge it.

A good fit when

Teams with a manual process to automate, a document base people struggle to search, or an existing product whose users now expect AI features.

  • Assistants that answer from your own documents and cite the source
  • Agents that act inside your CRM, ERP or helpdesk with human approval steps
  • Models monitored for drift and retrained on a schedule

  • A rule or a report would do

    If the logic fits in a few clear rules, or people just need a better dashboard, AI adds risk without adding value. We will build the simpler thing.

  • There is no data and no test set

    Without examples of good outputs, nobody can tell whether the AI works. We start with AI Consulting and a small labelled set first.

  • Every answer must be 100% correct with no review

    Generative AI is probabilistic. Where errors are unacceptable, we design human approval steps or recommend deterministic software instead.

Selected work

AI & Intelligent Solutions in production

Platforms where these services are running today. See all work

Related

Where AI & Intelligent Solutions fits in

Industries

Solutions built on these services

Prefer engineers in your own team?

FAQ

Frequently asked questions about AI & Intelligent Solutions

What AI services does O Clock Software provide?

O Clock Software provides 14 AI services, from deciding what to build to keeping models accurate in production. They are AI consulting, AI development, generative AI, LLM applications, RAG knowledge assistants, AI agents, chatbots, voice and document AI, computer vision, predictive analytics, machine learning, AI for existing products, AI integration and MLOps.

What is the difference between generative AI and machine learning?

Machine learning learns patterns from historical data to predict or classify, such as forecasting demand; generative AI produces new text, images or code, such as drafting a reply. Many production systems combine both, for example a model that scores risk and an LLM that explains the score in plain language.

What is a RAG knowledge assistant?

A RAG (retrieval-augmented generation) assistant answers questions by first retrieving relevant passages from your own documents and then generating an answer grounded in them, with citations. It keeps answers current without retraining a model and respects who is allowed to see which documents.

Can you add AI to our existing software without rebuilding it?

Yes. We usually add AI as a separate service connected to your product through APIs, so features such as search, summarisation, assistants or predictions can ship one at a time without changing your core system.

How do you measure whether an AI system is working?

We agree measurable criteria before building, such as answer accuracy on a test set, share of tasks completed correctly or time saved per case, and evaluate every release against them. After launch, monitoring tracks accuracy, drift and user feedback so problems surface early.

How do you keep our data secure when using LLMs?

We use enterprise API terms that exclude your data from model training, apply role-based access to retrieved documents, mask sensitive fields where needed, and can deploy open-source models in your own cloud when data must not leave it.

Which AI models do you work with?

We work with commercial models such as GPT, Claude and Gemini, open models such as Llama and Mistral, and classic machine learning frameworks such as PyTorch and scikit-learn. We choose per use case based on accuracy, latency, data residency and long-term maintainability.

Do you provide AI consulting before development?

Yes. AI Consulting is a short engagement that scores candidate use cases, checks data readiness and feasibility, and ends with a written recommendation, including when an off-the-shelf tool or a non-AI solution is the better choice.

Other service areas

Most projects combine three or four areas

One team, one delivery lead, across all of them. See all services

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MAIL US info@oclocksoftware.com
TEAMS oclocksoftware
REACH US +91-44-42089942 +91-44-28279942