AI Services

Cut through the AI hype with a partner who helps you identify what to build, brings it to life fast, and makes sure it sticks. From MVP to enterprise-scale rollout, we engineer for value, speed, and adoption.

Solving Today's Business Challenges with AI

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AI-Enabled Engineering

Accelerate delivery, reduce rework, and code with confidence using AI-enabled development workflows. Our AI-enabled workflows embed intelligence across the lifecycle to help teams build faster, maintain standards, and scale development without friction or compromise.

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Agentic AI

Design AI agents that reason, plan, and act autonomously. Unlike rule-based systems, they adapt in real time, use context to make strategic decisions, and solve complex business problems — powering proactive, self-improving automation across your operations.

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Generative AI

Transform how your business creates, personalizes, and applies knowledge — from delivering tailored customer experiences and generating new content to accelerating decision-making. Eliminate manual work, speed up operations, and unlock new revenue opportunities with Gen AI.
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Conversational AI

We turn conversations into impact. Our Conversational AI solutions automate customer interactions, improve service experiences, cut operational costs, and drive business KPIs — all seamlessly integrated into your existing workflows. Always available 24/7. They don't sleep, they don't take breaks.
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MLOps

We help you get AI into production faster — and keep it working reliably. Our MLOps frameworks make it easier to deploy models, avoid performance issues, and scale AI across your business without delays or breakdowns.
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Responsible AI

Build AI systems that are explainable, fair, and aligned with global regulations - enhancing trust, safeguarding data, and optimizing decision-making while maintaining security, accountability, and operational resilience in an evolving AI landscape. 

Our Approach

Assessment And Opportunity Scan Assessment And Opportunity Scan hover Running AI Technology Assessment & Opportunity Scan

We evaluate potential use cases, align AI strategy with your business goals, and prioritize opportunities through collaborative workshops. Our process includes vendor selection, tech familiarization, roadmap creation, and a detailed assessment report with use case lists and business cases.

Assessment And Opportunity Scan
Piloting and Integration Piloting and Integration hover Executing Piloting & Integration

Building on the AI strategy and roadmap, we run pilot projects to validate use cases, define security needs, and document operational frameworks. We assess infrastructure and architecture readiness, laying the groundwork for seamless integration, scalability, and long-term success with structured, accessible custom data.

Piloting and Integration
Custom Data and Live Data-1 Custom Data and Live Data hover Preparing Custom Data & Connecting Live Data

We identify, connect, and manage both historical and real-time data sources to prepare your LLM for intelligent action. By creating contextual awareness through structured data integration, we ensure the AI understands patterns, behaviors, and events — enabling accurate, timely responses and continuous learning within your workflows.

Custom Data and Live Data
Fine Tuning and Complex Prompt design Fine Tuning and Complex Prompt design hover Fine-Tuning & Complex Prompt Design

We design prompts, engineer economic token usage, and test LLM variants. Restrictions, A/B testing, and “used request–answer pair” analysis ensure a balance between speed, accuracy, and output reliability. 

Fine Tunning and Complex Prompt Design
Integration in complex workflows Integration in complex workflows hover Integration in Complex Workflows

We embed AI into critical business processes with custom model triggers, smart AI agents, and human-in-the-loop checkpoints. Our approach supports real-time monitoring, auditing, and access to tools. This ensures transparent oversight, process continuity, and adaptive exception handling throughout your AI-enabled workflows.

Integration in complex workflows
Operations & Institutionalization Operations & Institutionalization hover Operationalizing & Institutionalizing AI at Scale

We embed LLMs into enterprise architecture and governance frameworks — ensuring your systems evolve, not expire. From usage monitoring and data protection to model updates and cost control, we future-proof your AI to keep pace with innovation and avoid becoming legacy overnight.

Operations and Institutionalizations
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Running AI Technology Assessment & Opportunity Scan

We evaluate potential use cases, align AI strategy with your business goals, and prioritize opportunities through collaborative workshops. Our process includes vendor selection, tech familiarization, roadmap creation, and a detailed assessment report with use case lists and business cases.

Assessment And Opportunity Scan

Executing Piloting & Integration

Building on the AI strategy and roadmap, we run pilot projects to validate use cases, define security needs, and document operational frameworks. We assess infrastructure and architecture readiness, laying the groundwork for seamless integration, scalability, and long-term success with structured, accessible custom data.

Piloting and Integration

Preparing Custom Data & Connecting Live Data

We identify, connect, and manage both historical and real-time data sources to prepare your LLM for intelligent action. By creating contextual awareness through structured data integration, we ensure the AI understands patterns, behaviors, and events — enabling accurate, timely responses and continuous learning within your workflows.

Custom Data and Live Data

Fine-Tuning & Complex Prompt Design

We design prompts, engineer economic token usage, and test LLM variants. Restrictions, A/B testing, and “used request–answer pair” analysis ensure a balance between speed, accuracy, and output reliability. 

Fine Tunning and Complex Prompt Design

Integration in Complex Workflows

We embed AI into critical business processes with custom model triggers, smart AI agents, and human-in-the-loop checkpoints. Our approach supports real-time monitoring, auditing, and access to tools. This ensures transparent oversight, process continuity, and adaptive exception handling throughout your AI-enabled workflows.

Integration in complex workflows

Operationalizing & Institutionalizing AI at Scale

We embed LLMs into enterprise architecture and governance frameworks — ensuring your systems evolve, not expire. From usage monitoring and data protection to model updates and cost control, we future-proof your AI to keep pace with innovation and avoid becoming legacy overnight.

Operations and Institutionalizations

Industries We Serve

Banking & Financial Services
Banking & Financial Services

Enhance fraud prevention, automate decisions, and elevate service with secure, AI-driven financial intelligence.

Healthcare & Life Sciences
Healthcare & Life Sciences

Improve diagnostics, streamline care, and accelerate research through predictive analytics and AI-powered automation.

Hi-Tech Services
Hi-Tech Services

Accelerate development cycles and ensure quality with AI-powered automation, real-time testing, and intelligent debugging.

Retail & Consumer Goods
Retail & Consumer Goods

Deliver hyper-personalized experiences, streamline supply chains, and boost conversions with real-time insights and predictive AI.

Travel & Hospitality
Travel & Hospitality

Personalize journeys, automate operations, and forecast demand with AI for smoother, more memorable travel experiences.

Automotive & Manufacturing
Automotive & Manufacturing

Boost efficiency, predict failures, and optimize output with AI-driven automation and real-time production intelligence.

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15+
development centers
20+
offices globally
4,000+
IT professionals

What our customers say

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Our clients

From global enterprises to digital disruptors, we've partnered with companies for over 20 years to reimagine, reshape and redefine the way people experience your business.

FAQs on AI Services

Can you develop a custom AI model tailored to our unique dataset and specific business objectives?

Yes. We build AI solutions that are fully aligned with your business objectives, proprietary data, and operational workflows. Once we identify the highest-impact use cases, we run focused discovery sprints to validate feasibility, then rapidly develop and train models tailored to your specific goals. User feedback loops, built into the prototyping phase — ensure solutions are relevant, effective, and embraced by teams. We emphasize measurable outcomes from the outset, helping you maximize the ROI of your AI investment while maintaining alignment with broader digital transformation goals.

What is your approach to fine-tuning pre-existing AI models versus building entirely custom solutions, and how do you determine the best path for a client’s specific needs and budget?

We always begin with an assessment of your technical requirements, business objectives, and data sensitivity. From there, we recommend one of two routes: (1) fine-tuning powerful proprietary models (like GPT or Claude) via APIs or private cloud instances, or (2) customizing smaller, open-source or distilled models (e.g., LLaMA, DeepSeek) hosted in your own environment for greater control. In both cases, we tailor models using your data, ensure privacy through secure infrastructure, and often implement Retrieval-Augmented Generation (RAG) systems for contextual relevance. This approach ensures performance, security, and cost-effectiveness — without the need to build models from scratch.

How do you ensure the seamless and secure integration of the AI solutions you develop with our existing enterprise systems, databases, APIs, and operational workflows?

We design integrations to be frictionless, secure, and future-ready. Our engineers work with your existing stack — CRM, ERP, APIs, data lakes, using modular architectures, cloud-native tools, and secure pipelines to avoid disruption. Whether hosted in the cloud or on-prem, every integration is scoped to fit your infrastructure and governed by strict access controls, encrypted communication, and compliance frameworks. We also focus on interoperability from day one, ensuring your AI systems not only connect seamlessly but also scale with your operations and data sources over time.

What is your approach to ensuring the AI solutions are built with scalability and maintainability in mind from the outset?

We architect AI systems for long-term sustainability by adopting a loosely coupled, modular design. This allows individual components, especially models to be swapped, updated, or scaled independently, which is critical given the rapid evolution of AI technologies. We support this flexibility with CI/CD pipelines, microservices, and full MLOps capabilities to automate deployment, testing, and retraining. All codebases are documented and version-controlled to reduce technical debt. This ensures your solution is not only performant on day one, but also remains adaptable and cost-effective as your needs and the AI landscape evolve.

What is your methodology for continuously monitoring the performance of deployed AI models, and how do you proactively address common issues like model drift, concept drift, or degradation in accuracy over time?

Our monitoring framework combines real-time analytics, KPI tracking, and anomaly detection to ensure AI models continue performing as intended. For higher-stakes use cases, we embed “LLM as a judge” logic—where a separate AI system evaluates the output of the primary model — and escalate inconsistencies to a human in the loop. This layered oversight helps detect and respond to issues like model or concept drift before they impact outcomes. We also maintain retraining pipelines and version control so models can be iteratively improved with fresh data, ensuring sustained accuracy, business relevance, and compliance.

Let's talk about transforming your business, with no strings attached

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