Agentic AI

Agentic AI Development Company

Agentic AI to automate workflows and scale operations. We build custom AI agents that don’t just assist. They plan, decide, and drive business outcomes on their own.

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  • 16+ years engineering
  • 200+ in-house engineers
  • Secure, scalable AI solutions

Trusted By

750+ happy clients, including top Fortune 500 companies

The Agentic AI Revolution

What Makes Agentic AI Different?

Agentic AI represents a fundamental shift from reactive AI tools to autonomous intelligent systems that can perceive their environment, make decisions, and take actions to achieve specific goals without constant human supervision.

Agentic AI solutions operate independently as systems plan multi-step workflows, adapt to changing conditions, learn from outcomes, and execute complex business processes with minimal human intervention.

As an agentic AI development company, Sphinx Solutions specialises in building custom AI agents that don't just assist, they autonomously drive business outcomes. Our agentic AI software development approach pairs proven frameworks with domain-specific customisation for every engagement.

Designed for autonomous execution

AI agents that don’t just assist but plan, decide, and execute multi-step tasks independently, aligned with your business logic.

Orchestrated multi-agent systems

Collaborative AI agents working together across workflows, tools, and data to handle complex processes end to end.

Context-aware and continuously learning

Agents that retain context, adapt in real time, and improve decision-making with every interaction and data input.

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What We Build

Agentic AI Development Services

We build AI agents that don’t just assist. They act. Autonomous systems that integrate with your business to automate workflows and drive real results.

01

Custom AI agent development

We design and build tailored AI agents for your specific business requirements, from conversational assistants to complex decision-making systems that handle intricate workflows autonomously.

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02

Multi-agent systems & orchestration

Deploy coordinated networks of specialised AI agents that collaborate, share context, and execute parallel tasks. Our multi-agent systems ensure seamless orchestration across complex business processes.

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03

AI copilots & assistants

As a trusted ai copilot development company, we build ai agents for business teams that augment human expertise, offering real-time insights, automating repetitive tasks, and accelerating decision-making across sales, support, engineering, and operations.

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04

Autonomous workflow automation

Replace manual processes with intelligent automation that adapts to changing business conditions. As a form of agentic process automation, our AI workflow solutions handle everything from data processing to customer interactions without human oversight.

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05

LLM integration & fine‑tuning

Leverage cutting-edge large language models from OpenAI, Anthropic, and open-source alternatives. We customise and fine-tune LLM-powered agents to align perfectly with your domain expertise and compliance requirements.

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06

Human-in-the-loop AI systems

Design hybrid systems where AI agents handle routine decisions while escalating critical situations to human experts. This approach balances automation efficiency with human judgment where it matters most.

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What We Solve

Agentic AI Solutions

AI agents that evaluate options, weigh trade-offs, and make intelligent decisions aligned with your business objectives.

Plan and execute complex workflows spanning multiple systems, APIs, and decision points without human intervention.

Maintain conversation history, learn from interactions, and build contextual understanding across sessions.

Seamlessly connect with your existing tech stack: CRMs, databases, communication tools, and business applications.

Continuously improve performance based on feedback loops, outcomes, and changing business conditions.

Built on cloud-native infrastructure that handles enterprise-scale workloads with reliability and performance.

How We Work

Custom Agentic AI Development Process

Our Agentic AI lifecycle is designed to build autonomous, decision-making systems with clarity, speed, and zero guesswork. From discovery to deployment, every step ensures your AI agents are aligned with real business outcomes.

  1. Step 1

    Discovery & requirements analysis

    What we do: We analyse your business workflows, identify automation opportunities, and define where agentic AI can deliver the most impact. Through stakeholder interviews, process mapping, and feasibility studies, we establish clear goals and technical direction.

    What you get

    • Defined AI agent use cases and business objectives.
    • Workflow mapping and automation opportunities.
    • Feasibility assessment and risk analysis.
    • Project scope, timeline, and cost estimation.

  2. Step 2

    Architecture design & planning

    What we do: Our architects design the foundation of your agentic system, selecting the right models, frameworks, and integrations, and defining agent behaviours, decision logic, data flows, and scalability.

    What you get

    • Complete system architecture blueprint.
    • Agent capability and decision-making framework.
    • Integration and data flow design.
    • Security, compliance, and scalability plan.

  3. Step 3

    Prototype development & training

    What we do: We build a functional prototype within weeks to demonstrate core agent capabilities and workflows, allowing early interaction, feedback, and validation before scaling further.

    What you get

    • Working AI agent prototype.
    • Early-stage workflow validation.
    • Feedback-driven iteration cycles.
    • Reduced development risk and faster alignment.

  4. Step 4

    Integration & customisation

    What we do: We integrate AI agents into your existing systems, including CRMs, ERPs, databases, APIs, and communication tools. Agents are trained on your data and customised to match your business logic.

    What you get

    • Seamless integration with your tech stack.
    • Domain-trained and customised AI agents.
    • API and third-party system connectivity.
    • Human-in-the-loop workflows for critical tasks.

  5. Step 5

    Quality assurance & security hardening

    What we do: We rigorously test your AI agents for performance, reliability, and security. This includes functional testing, edge case validation, and security audits to ensure enterprise readiness.

    What you get

    • Performance and accuracy validation reports.
    • Edge case and stress testing results.
    • Security audit and compliance checks.
    • Production-ready, reliable AI systems.

  6. Step 6

    Deployment, training & ongoing support

    What we do: We deploy your agentic AI systems with monitoring and logging in place. Your team is trained to manage and optimise agents, while we provide continuous support and improvements.

    What you get

    • Production-ready AI deployment.
    • Monitoring, logging, and alert systems.
    • Team training and documentation.
    • Ongoing support, updates, and optimisation.

Proof Of Work

AI Projects That Delivered Measurable Results

Every solution we build is AI-ready by architecture, so your business grows smarter. We engineer software around the way your business, processes, integrations, and growth targets. We bring years of delivery precision to every project across the world.

The No Stress Impress app shown on a phone

NO STRESS IMPRESS

AI-powered student productivity and mental wellness platform

Problem

Students struggled to balance academics, deadlines, and mental well-being. Existing tools were too generic or lacked personalisation, causing low engagement, poor productivity, and ineffective stress management.

Challenge

To build an AI-driven platform that manages tasks and schedules while understanding user behaviour, stress patterns, and productivity gaps, ensuring a simple, engaging, and personalised experience for students.

Solution

Developed an AI-powered mobile platform with task planning, mood tracking and behavioural insights, integrating smart recommendations and analytics to enhance productivity, engagement, and consistency.

The Koras.ai encrypted email interface on a laptop

KORAS.AI

Zero-plugin AI email encryption platform

Problem

Email communication lacked simple encryption. Existing solutions required plugins, technical setups, or complex workflows, making secure communication inaccessible, inconvenient, and difficult for everyday users globally.

Challenge

Design an AI-powered encryption system working directly within existing email platforms, eliminating the need for installations, integrations, or training while maintaining simplicity, usability, and strong security standards.

Solution

Developed an AI-based encryption platform enabling users to secure emails by adding brackets in the subject line, automating encryption, decryption, and key management without disrupting existing workflows seamlessly.

The ProMarketer.ai campaign dashboard on a laptop

PROMARKETER.AI

AI-driven marketing automation and optimisation platform

Problem

Marketers struggled to manage campaigns across platforms, analyse performance data, and optimise ads in real time. Manual processes led to inefficiencies and missed growth opportunities.

Challenge

To create a centralised AI platform that automates campaign management, delivers actionable insights, and continuously optimises marketing performance across multiple channels.

Solution

An AI-powered marketing automation system with campaign tracking, audience segmentation, and real-time optimisation, plus performance dashboards and smart recommendations to maximise ROI.

Comparison

Agentic AI vs Traditional AI

Both are called AI, and they behave nothing alike once a workflow gets complicated. Here is where the difference actually shows up.

Aspect Agentic AI Traditional AI
Core intelligence & functioning Operates as an autonomous, goal-driven system that can plan, reason, and execute multi-step tasks independently. It doesn’t just respond, it decides what needs doing next and adapts based on outcomes. Primarily reactive and task-specific. It follows predefined models, rules, or training data to generate outputs, but does not independently plan or adapt workflows beyond its programmed scope.
Decision-making & autonomy Capable of autonomous decision-making with minimal human input. It evaluates context, breaks down complex objectives, and chooses optimal action paths dynamically. Requires human-defined inputs, prompts, or rules. It cannot independently manage end-to-end processes or adjust decisions beyond its training limitations.
Workflow execution Handles multi-step, interconnected workflows by orchestrating multiple agents or tools, suiting complex business processes like automation, research, and operations. Typically executes single-step or narrowly defined tasks (classification, prediction, simple automation) without cross-task coordination.
Learning & context awareness Continuously adapts using contextual memory and environmental feedback, improving across tasks over time and adjusting strategies dynamically. Learns during training but remains static in deployment. It lacks real-time adaptability unless retrained or fine-tuned.
Tool & system integration Integrates with APIs, databases, external tools, and other AI agents to complete goals, functioning as a connected intelligent ecosystem. Integration is possible but usually limited to predefined pipelines or fixed integrations, requiring manual configuration and updates.
Error handling & self-correction Can self-evaluate outcomes, detect errors in workflows, and retry or adjust strategies autonomously to improve success rates. Error handling is mostly external, requiring human monitoring, debugging, or rule-based fallback systems.
Scalability & enterprise use Highly scalable for enterprise-grade automation: autonomous operations, AI-driven decision systems, intelligent assistants, and multi-domain workflows. Best suited to isolated applications, chatbots, recommendation systems, forecasting models, task-specific automation.
Operational intelligence A shift towards AI agents that act like digital workers, thinking, planning, and executing as semi-independent systems. A tool-based intelligence system that enhances human decision-making but does not operate independently.

Sources: Stanford University, AI Index and autonomous systems research. Last updated: 12 June 2026

Expert Insights

Agentic AI is changing how companies automate work. Earlier, systems followed fixed steps and could only do what they were programmed for. Now AI agents can plan tasks, adjust when things change, and handle multiple steps together. Automation is becoming more independent, where systems make decisions, adapt in real time, and work towards better results on their own instead of just reacting.
Anand Mahajan CEO, Sphinx Solutions

How We Engage

Engagement Models That Fit Your Agentic AI Project

Every Agentic AI project is different; some need full-scale ownership, others need speed, flexibility, or expert augmentation. We offer engagement models designed to match your goals, timelines, and level of control.

01

Dedicated AI team

A fully committed team working exclusively on your agentic AI project. Ideal for long-term builds and complex multi-agent systems.

02

Project-based model

End-to-end development with a fixed scope, timeline, and cost. Best for clearly defined agentic AI use cases.

03

Staff augmentation

Extend your in-house team with specialised AI experts. Perfect for faster execution without full hiring.

04

Consulting & strategy

Expert guidance to plan and validate your agentic AI roadmap. Ideal for early-stage exploration and decision-making.

Not sure which model fits your AI project stage?

Book a 30-minute engagement consultation.

Free consultation

How We Build It

Agentic AI Technology Stack

The models, frameworks, and infrastructure our agents are built on, each chosen for the job in front of it rather than out of habit.

  • GPT‑4o
  • Claude
  • Llama 3
  • Mistral AI
  • Gemini

Industries

Agentic AI Development Across Industries

Why Choose Us

Client-Oriented. On-Time Delivery.

16+

Years of experience

Sphinx has completed 16 successful years in the industry, helping businesses with technology and digital transformation, including AI-powered solutions across major industry verticals.

16+

Industry experts

We have a dedicated and reliable team of AI engineers, ML scientists, data engineers, and MLOps specialists covering every role in the AI development lifecycle.

1500+

Solutions delivered

We have delivered more than 1,500 solutions through a results-driven approach, many to recurring clients who keep expanding their AI capabilities with us.

200+

In-house resources

We have a dedicated in-house team, experienced and skilled across AI development, software engineering, QA, DevOps, and cloud infrastructure.

750+

Happy clients

We are trusted by 750+ clients for best-in-class AI solutions at competitive rates, with the delivery accountability enterprise clients demand.

50M+

Users love our work

Our client-centric approach and high-calibre AI engineering, built on current models and frameworks, have made us a trusted partner for businesses building AI.

Highly Rated Across Top Platforms

Connect with us

Turn Your Ideas Into Reality. Let’s Connect and Create Something Groundbreaking.

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Frequently Asked
Questions

Everything you need to know about building agentic AI with us. Can’t find your answer? Talk to us.

Agentic AI tackles the things that quietly slow a business down: manual workflows, slow decisions, systems that don’t talk to each other, and repetitive busywork. The difference from ordinary automation is that it can reason about a task, work across several tools, and carry a process through without someone watching every step.

RPA follows fixed rules to handle repetitive, structured jobs like data entry or filling in forms. Agentic AI goes further: it understands the goal, makes decisions along the way, and copes with workflows that change as they run. Put simply, RPA does the task you scripted, while agentic AI runs the whole process and adapts.

Yes. It connects to APIs, CRMs, databases, cloud platforms, and other enterprise tools. Because it is built to work across several systems at once, it fits companies that already have a lot of digital infrastructure in place. Instead of replacing what you run, it sits on top and coordinates between your existing tools.

Often, yes. Chatbots and automation tools tend to handle one task or one conversation at a time. Agentic AI takes on a full workflow, makes decisions, and coordinates several steps across different systems on its own. It is less a single feature and more something that manages the whole job from start to finish.

We build agentic AI systems that cut operational costs and take repetitive work off your team. They make decisions in real time, scale as your workflows grow, and connect to the systems you already run. We start by finding where your team loses the most time, then build around those points first.

It depends on complexity. A simple workflow can be up and running in a few weeks, while an enterprise-grade multi-agent system can take several months. Either way, the work covers planning, integration, testing, and deployment. We scope the timeline with you up front so there are no surprises partway through.