Top 10 AI Consulting Companies to Consider in 2027
Key Takeaways: AI consulting companies assist startups and enterprises in converting AI experiments into measurable business outcomes with the right
Azure AI Consulting and Development Services
PSSPL builds and manages AI solutions on Microsoft Azure for mid-sized and enterprise organizations across the UK, EU, and US. With over 26 years of experience in software and AI engineering, we’ve collectively served more than 500 customers and delivered over 1,000 projects.
Solutions Partner: Data & AI (Azure) | Solutions Partner: Digital & App Innovation (Azure) | ISO/IEC 27001:2022 | ISO 9001 | SOC 2 Type II
500+
Customers
•
1000+
Projects
•
250+
Employees
•
26+
Years of Experience
•
Azure AI Consulting Expertise You Can Rely On
PSSPL combines Microsoft Azure expertise with hands-on AI engineering experience to help businesses plan, develop, and deploy AI solutions.
28 engineers
Microsoft-certified engineers with 57 Microsoft certifications collectively
2 Partner
Microsoft Solutions Partner designations in Data & AI and Digital & App Innovation
More than 2 decades
of software engineering experience, backed by a dedicated AI and ML practice
MVP Community
Part of one of the largest Microsoft user communities, which includes Microsoft MVPs
Certified team
9 Azure Developer (AZ-204) | 6 Azure AI Engineer (AI-102) | 5 Azure Solutions Architect Expert (AZ-305) | 5 Azure Administrator (AZ-104) | 3 Azure Data Scientist (DP-100) | 2 DevOps Engineer Expert (AZ-400) | 1 Azure Security Engineer (AZ-500) | 5 Power Platform Developer, Consultant and Architect
What Does an Azure AI Consulting Partner Do?
As an Azure AI consulting and development partner, the agenda is simple: help businesses find the right AI opportunities, plan out their solutions, and put them into practice with Microsoft Azure. This involves selecting AI models, building AI agents, connecting business data, and setting up security and governance. Prakash Software helps businesses transition from initial planning up until deployment, with solutions specifically designed around the brand’s vision, data, and existing systems.
How We Build AI on Microsoft Azure
Each AI project requires a different mix of services. We bring together the best-suited models, agents, data tools, and security controls to develop an app or agent that goes well with your business.
Layer 1
End result: Your team can easily use AI in familiar tools or apps.
Apps and Channels
We bring AI into tools and apps that your department already uses, for instance, Teams or M365 Copilot. For specific needs, we also create customized web and mobile apps.
Microsoft 365 Copilot | Microsoft Teams | Web and mobile apps
End result: Your team can easily use AI in familiar tools or apps.
Layer 2
Outcome: Agents take care of regular tasks while people stay in control of exceptions and important decisions.
AI Agents
Our Azure AI specialists create AI agents that can handle tasks, use integrated tools, and work seamlessly with your business systems. As needed, agents can hand over tasks directly to your department for further assistance.
Microsoft Foundry Agent Service | Microsoft Agent Framework | Business system integrations | Voice and chat agents
Outcome: Agents take care of regular tasks while people stay in control of exceptions and important decisions.
Layer 3
Outcome: Staff can find relevant data faster and verify answers against their original sources.
Knowledge and Retrieval
We connect AI to your essential business documents and data with the help of Azure AI Search and Foundry IQ. This allows agents to find relevant information and give answers grounded in your content.
Azure AI Search | Foundry IQ | Hybrid and semantic search | SharePoint and other data sources
Outcome: Staff can find relevant data faster and verify answers against their original sources.
Layer 4
What happens next: Less manual work on everyday documents, calls, and image processing, with staff reviewing exceptions if and when required.
Prebuilt AI Services
When Microsoft already provides a service for the job, we leverage it instead of starting from scratch. These tools can extract data from documents, process speech, translate text, analyze language, and understand images.
Document Intelligence | Speech | Translator | Language | Vision | Content Understanding
What happens next: Less manual work on everyday documents, calls, and image processing, with staff reviewing exceptions if and when required.
Layer 5
Outcome: You can choose models based on their performance, cost, and suitability for the task instead of relying on just one provider.
AI Models
Microsoft Foundry gives us access to models from OpenAI, Anthropic, Meta, Mistral, and other providers. We assess the options for your use case and can design your solution to support model changes where practical.
Azure OpenAI models | Anthropic Claude | Meta models | Mistral models | Other hosted and open models
Outcome: You can choose models based on their performance, cost, and suitability for the task instead of relying on just one provider.
Layer 6
End result: Custom models can be deployed and maintained through a consistent, controlled process.
Custom Machine Learning
Some business problems require models trained especially on your own, everyday data. We use Azure Machine Learning or Azure Databricks to develop and manage those models effectively, with processes for testing, deployment, versioning, and monitoring.
Azure Machine Learning | Azure Databricks | MLOps pipelines | Model evaluation and monitoring
End result: Custom models can be deployed and maintained through a consistent, controlled process.
Layer 7
Outcome: Your team gains better control over data access, permissions, security risks, and governance as the application moves into production.
Data, Security, and Governance
AI requires reliable data and the right safeguards. Our Azure AI experts leverage Microsoft Fabric and OneLake for data foundations, alongside tools for identity, access, governance, monitoring, and AI safety.
Microsoft Fabric and OneLake | Microsoft Entra ID | Microsoft Purview | Microsoft Defender for Cloud | Azure AI Content Safety
Outcome: Your team gains better control over data access, permissions, security risks, and governance as the application moves into production.
Why Choose Microsoft Azure for AI Consulting?
Microsoft Azure gives businesses a practical foundation for creating AI solutions that fit their current business systems, security needs, and business objectives. With the right Azure AI consulting approach, you can put AI to work without adding unnecessary complexity.
AI solutions built with Azure connect seamlessly with apps such as Microsoft Entra ID, Teams, and other Microsoft 365 tools. As a result, businesses can easily connect any AI applications or tools to their available workflows while keeping access aligned with user identities and permissions.
Microsoft Foundry gives access to models from OpenAI, Anthropic, Meta, Mistral, and other providers. Our Azure AI consulting services experts help you select models that suit your use case, performance needs, and budget.
Azure can safeguard sensitive business information and manage access efficiently. Our Azure specialists help configure the right identity controls, network settings, and governance measures to meet your firm's needs.
Azure unifies various AI models, agents, data services, and security tools. Our experts set things up very effectively, making it easier to manage. We ensure that the funds are only processed as per requirements and that AI solutions keep up with your business requirements.
What’s New in Microsoft Azure AI?
Over the years, Azure AI has changed exponentially. New models, agent development tools, and tactics to connect AI with business applications. Here are the core updates from 2025 and 2026 that could help shape your AI strategy.
26 FEB 2025
EU Data Boundary Completed
Microsoft finished the EU Data Boundary for MS 365, Dynamics 365, and major Azure services, green signaling European organizations far better control over where their data is processed and stored.
18 NOV 2025
Claude Models Arrive in Microsoft Foundry
Claude models become available in public preview via Microsoft Foundry, expanding the choice of AI models businesses can use.
APR 2026
New Tools for Building and Running AI
Microsoft Agent Framework 1.0 became generally available for .NET and Python, along with Foundry Local. They open the path for more ways to create AI agents and run AI models locally for developers.
24 APR 2026
GPT 5.5 Comes to Microsoft Foundry
GPT 5.5 was added to Microsoft Foundry, giving businesses another model option for building AI apps.
2 JUN 2026
Foundry IQ and Developer Tools Advance
At Microsoft Build, Foundry IQ knowledge bases and the Foundry Toolkit for VS Code became generally available, making it easier to create AI-powered apps grounded in reliable knowledge and simplify development workflows.
10 JUN 2026
AI Agents Connect With Microsoft 365 Copilot and Teams
Publishing Foundry agents to Microsoft 365 Copilot and Teams becomes generally available, easing the process to bring custom AI agents into familiar work environments.
9 JUL 2026
More Model Options Listed on Azure
GPT-5.6, with Sol, Terra, and Luna tiers, appeared in Azure’s model catalogue, giving businesses more options to consider when choosing models for their AI solutions.
29 Jul 2026
Azure AI Adoption Continues to Grow
Microsoft reported 43% Azure growth and 1,00,000 Foundry customers in its fiscal Q4 2026 results, reflecting a robust demand for cloud and AI services.
17-20 Nov 2026
Microsoft Ignite 2026 – Upcoming
Microsoft Ignite is scheduled for San Francisco from 17 to 20 November. New announcements might bring further changes to Azure AI, models, and agent development.
What the Latest Research Says About Enterprise AI
These reports highlight the returns enterprises expect from AI, how fast adoption is growing, and the risks of investing without giving a second thought. We leverage these findings to help shape practical AI strategies and develop business cases.
Generative AI Returns
$3.70 for every $1 invested
Businesses reported an average return of $3.70 for every dollar invested in generative AI, with top companies reporting returns close to $10.
Source: IDC study commissioned by Microsoft, November 2024
Growing Interest in AI
82% of Leaders
In Microsoft's 2025 survey, 82% of business leaders expected to use AI-driven solutions within the next 1-1.5 years.Source: Microsoft 2025 Work Trend Index, April 2025
The Risk of AI Agent Projects Failing
More than 40% at risk of cancellation
Gartner predicted that over 40% of agentic AI projects could be cancelled by the end of 2027, most probably because of surging costs or unclear business value. Clear goals and well-thought-out planning can help organizations avoid these pitfalls.
Source: Gartner, June 2025
Microsoft Foundry Adoption
1,00,000 organizations
Microsoft reported that 1,00,000 enterprises were using Microsoft Foundry alongside 43% year-over-year Azure growth in its fiscal Q4 2026 results.
Azure Security and Governance, Build Around Your Needs
Microsoft provides security tools within Azure, but they need to be set up correctly. As your Azure AI development partner, Prakash Software Solutions helps you protect business data, have control over access to AI systems, and address relevant compliance needs.
What Microsoft Azure Provides
- Compliance support: Azure provides certifications and resources that allow businesses to meet industry and regulatory requirements.
- Data residency: Microsoft’s EU Data Boundary helps eligible customers keep and process certain data within the EU, subject to service terms.
- Data privacy: Prompts and responses aren’t used to train foundation models without permission.
- Security tools: Azure offers tools to detect any threats, monitor AI data use, and protect AI apps.
How PSSPL Secures Your AI Solutions
- Secure connections: Our experts restrict public access to AI models, search services, and data stores wherever private networking is required.
- Access control: We use Microsoft Entra ID to manage who can access your AI systems and managed identities to let apps connect securely.
- Data protection: We use Key Vault to safeguard sensitive credentials and set permissions so people and apps only access what they require.
- Monitoring and compliance: Our Azure specialists help you choose suitable Azure regions, track AI activity, test outputs, and document the controls necessary to support your compliance needs.
Azure Machine Learning, Databricks, or Microsoft Foundry?
A common enterprise setup comprises Databricks for data and model training, Azure ML for managing custom models, and Foundry for building AI agents and GenAI apps around them.
Azure Databricks
Typical Use Case:
There are numerous use cases of Databricks; some of the most common ones are Mosaic AI, Unity Catalog governance, Lakehouse-scale data engineering, and ML/GenAI training.
Well suited for:
Azure Databricks is the best choice when it comes to feature engineering, large-scale training, and data-first teams.
Azure Machine Learning
Typical Use Case:
AzureML use cases comprise AutoML, full MLOps, and custom model training.
Well suited for:
It is best suited for classical ML and DL with governed, repeatable pipelines.
Microsoft Foundry
Typical Use Case:
Their use cases include pre-built models, generative AI apps, and agents with proper governance.
Well suited for:
It works best for GenAI & agents – Foundry Models / Foundry IQ.
The Models We Build
Enterprise AI isn’t just about agents and chatbots. In many cases, businesses still need models that can learn from their data, spot patterns, and predict what’s about to happen next.
AutoML & Custom Models
With the help of AutoML, businesses can speed up initial stages of model development, while custom models make sense when off-the-shelf options don’t fit right.
Deep Learning
When it comes to complex tasks such as image recognition or natural language processing, deep learning powers those apps efficiently.
Recommendation System
These models learn from customer behavior to suggest content, products, or the next best action.
Fraud & Anomaly Detection
Models can flag unusual patterns or suspicious activities, helping businesses detect potential fraud or other issues as they happen.
Forecasting
Organizations can use historical data to forecast demand, revenue, inventory needs, and capacity.
Predictive Models
From customer churn and credit risk to pricing and demand, these models assist businesses in making more informed, data-backed decisions.
The MLOps Lifecycle We Deliver
A model only turns out to be useful when it can work reliably in production. We develop the processes necessary to efficiently deploy, manage, monitor, and update models over time.
Prepare data and create reusable features with Fabric or Databricks, keeping training and production data consistent.
Train models, test different approaches, and track experiments with MLflow so results are easier to compare and reproduce.
Version models and manage approvals, access, and model history through MLflow and Unity Catalog.
Deploy models via online endpoints for real-time predictions or batch endpoints for large-scale scoring.
Track model performance, data quality, and drift, with alerts when something needs attention.
Set up automated retraining and CI/CD pipelines to keep models accurate as data and business needs change.
Our Azure AI Consulting and Development Services
We help you choose the right AI models, develop safe apps, and connect AI with your business data using Microsoft Azure.
Azure OpenAI and Foundry Models
Develop AI apps, copilots, and agents with the help of GPT, Claude, and other models available via Microsoft Foundry. We help you choose the ideal models and manage their performance and expenses.
Azure AI Search and Foundry IQ
Help AI find the right information across your business data with smart search, relevant results, and shared knowledge sources for AI agents.
Azure AI Services and Foundry Tools
Use AI to process documents, comprehend speech, assess images, interpret language, and translate content for everyday business tasks.
Azure Machine Learning and MLOps
Train custom ML models, deploy them into production, and monitor their performance with tools such as Azure Machine Learning and Databricks.
AI Agent Development
Build AI agents that can use tools, handle multi-step tasks, and connect with business apps, including Microsoft 365 Copilot and Teams.
RAG Development
Connect AI models to your business documents and data so they can deliver more relevant, source-backed answers rather than relying only on their training.
AI Security, Governance, and Compliance
Safeguard AI apps with appropriate access controls, security reviews, responsible AI practices, and documentation to support compliance needs.
Business Intelligence and Analytics on Fabric
Bring business data together with Microsoft Fabric, OneLake, and Power BI to support reporting, analytics, and data-driven AI apps.
What We Build With Azure AI
Explore practical AI solutions for day-to-day business operations, from finding information and processing documents to automating tasks and analyzing data.
Knowledge Copilot for SharePoint
Azure AI Search & Foundry IQ:
Team members find answers to any questions that lie between company policies, contracts, and project files, with links to the original sources. The only demand is simply asking the right question.
Automated Invoice and Claims Processing
Azure AI Services & Foundry Tools:
Crucial information can be extracted from invoices and claims with the help of Azure AI. It also helps check records against business rules. If any issue comes up, it’s flagged for relevant staff to review.
Voice AI for Contact Centers
AI Agent Development:
AI agents can handle, transcribe, and translate everyday calls and conversations efficiently. They can also forward hard, complex inquiries to staff with a quick summary of what happened.
Demand Forecasting
Azure Machine Learning & MLOps:
Custom AI models analyze sales and operational data to forecast demand, helping businesses plan stock, resources, and operations.
Field Service Agents in Teams
AI Agent Development:
Technicians can use Teams to find procedures, check parts and job history, and update work orders via an AI agent.
Conversational Business Analytics
BI & Analytics on Fabric:
Business users can ask questions in plain, simple language and find answers based on company data in Microsoft Fabric and OneLake.
From First Assessment to Ongoing Support
Our experts at Prakash Software Solutions assist you from identifying the best-suited AI opportunities to building, designing the visuals, launching, and effectively managing Azure AI applications that go well with your business requirements.
Azure AI Readiness Assessment
We take a closer look at your goals, data, security needs, and existing Microsoft licences, in order to share a complete review of where it stands from a business perspective. You receive a clear list of AI opportunities, the Azure services required, and the key risks to address.
Proof of Value on Your Data
Our Azure engineers create a functioning prototype using your data and an actual business use case. You can check how it works against requirements before taking the final call.
Production Build
We develop and test your AI agents, data retrieval, integrations, and security controls. Our experts also provide the documentation your security and compliance teams need.
Managed LLMOps and Support
We monitor AI performance, expenses, response times, and access. We manage updates via a tested release process and offer ongoing support and regular reviews of results.
Microsoft Partner Funding
Curious whether your crafted Azure AI project is qualified for Microsoft funding programs such as Azure Accelerate?
How We Deliver Azure AI Projects at PSSPL?
Our five-step process takes your AI project from initial planning to production and ongoing support, with your approval at each key stage.
Assess
Initially, our experts would review your business goals, provided datasets, security needs, and available Microsoft agreements to find more suitable AI use cases and potential risks.
Design
We plan your Azure AI architecture, including models, data access, integrations, and security. You approve the design before development begins.
Prove
We develop a working prototype for one use case and test it against agreed success criteria. You can then decide whether to move ahead.
Manage and Support
We monitor performance, manage model updates, and provide ongoing support.
Build and Test
We build the production solution, test its performance and security, and add the necessary checks and monitoring. Your security and compliance teams review it before launch.
Why Choose PSSPL for Azure AI?
Our teams bring Microsoft expertise, top certified engineers, trusted security standards, and access to renowned, high-performing AI models to develop solutions that fit your business requirements.
Microsoft Solutions Partner for Azure
PSSPL holds Microsoft Solutions Partner designations for Data & AI and Digital & App Innovation, covering AI development, AI engineering, and solution architecture.
Certified Azure Engineers
Our 28 Microsoft-certified engineers hold 57 Microsoft certifications, including credentials in Azure development, AI engineering, and solution architecture.
ISO 27001, ISO 9001, and SOC 2 Type II
Our certifications and audit reports support your vendor assessments and provide evidence of our approach to information security and quality management.
Choice of Leading AI Models
As an Anthropic Claude Partner and OpenAI Select Partner, alongside our Microsoft partnership, we help you choose models based on your use case, requirements, and budget.
Client Success Stories
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Planning Your Azure AI Project?
Tell us what you want to accomplish or which business process you would like to simplify. Our specialists will help you map out the right Azure AI services and put together a practical plan for your project that actually delivers results.
Frequently Asked Questions
Microsoft Foundry brings AI models, agents, and tools together in a unified platform, with over 10,000 models available. Azure OpenAI is part of Foundry, alongside models from Anthropic, Meta, Mistral, and others.
No. We work with a variety of open models such as Claude, Meta, Mistral, and many others, including OpenAI. Our Azure specialists choose based on your requirements and test results, while keeping future model changes in mind.
Our security team uses access controls, private networking, and tools such as Key Vault to safeguard your data. We also configure monitoring and permissions to help keep your AI systems secure.
Yes. We can integrate AI agents with Microsoft 365 Copilot and Teams, so your staff can easily leverage them in familiar tools with appropriate access controls.