Microsoft AI Solutions
Microsoft AI Solutions
We don't just add AI to software. We identify where intelligence can create measurable business value on the Microsoft stack, Azure AI, OpenAI, Copilot, and integrate it into the workflows your team already uses, from customer support to operations and reporting.
Azure AI & OpenAI • AI Agent Development • Microsoft Copilot Integration • RAG & Enterprise Knowledge • AI Workflow Automation
Grounded in your own data : AI that reasons from your actual business context, not a generic model's best guess.
Integrated where your team already works : No new platform to adopt, AI drops into the tools you already use every day.
Built to run in production : Monitored and maintained after launch, not a demo that quietly stops working.
Azure AI & OpenAI
If your systems are built on .NET, you don't need a separate Python stack bolted on just to add machine learning. We use Azure AI, OpenAI, and ML.NET, Microsoft's own framework, to build and integrate models directly into the applications you already have, one codebase, one deployment pipeline.
Chatbot development : Chatbots that resolve routine questions instantly and hand off anything complex to a human, so response times stay fast without added headcount.
Predictive analytics : Models built on your historical data that flag what's coming, so demand, pricing, and staffing decisions get made before the trend shows up in your numbers.
Natural language processing : Support tickets, reviews, and contracts get read automatically, surfacing sentiment, key terms, and translation at a volume no team could keep up with manually.
Computer vision : Quality control, inventory counts, and security review get an automatic first pass, flagging only what actually needs a human look.
Custom machine learning models : When your challenge is specific to your business, fraud patterns, customer segments, sales cycles, we build a model trained on your data instead of forcing your problem to fit someone else's.
We scope before we build : If a simpler rule-based fix solves your problem, we'll tell you that instead of selling you a model you don't need.
AI Agent Development
We build intelligent agents that understand business context, access your approved data, and perform real tasks across your applications, APIs, and workflows, not generic chatbots. Unlike a chatbot that only answers questions, an agent takes the next step, it acts on your data, calls your APIs, and completes the task instead of handing you an answer and stopping there.
Custom AI agent development : If scheduling, tier-one support, or a recurring internal process eats hours every week, we build an agent that takes that specific task off someone's plate.
Workflow automation agents : We connect agents to your CRM, ERP, and ticketing system so repetitive cross-system work happens automatically instead of by someone copying fields between tabs.
AI for document understanding : Invoices and contracts that someone currently keys in by hand can be read and structured automatically, OCR and NLP pull the fields out so your team reviews exceptions.
LLM integration and customization : A general-purpose model like GPT-4 or Claude doesn't know your product catalog or your policies until it's grounded in them, we fine-tune and integrate so responses reflect your business.
Built on OpenAI GPT, Claude, and custom-trained models : Whichever fits what the agent actually needs to do, not whichever is trending.
Access control built in : Data handling and explainability are built in from the start, so the agent holds up under your compliance review instead of becoming a problem after launch.
Microsoft Copilot Integration
Microsoft 365 Copilot out of the box is generic, it doesn't know your internal processes, your line-of-business systems, or the data sitting in your SharePoint sites and Dataverse tables until you connect it. We extend Copilot with custom plugins and connectors, and build purpose-specific copilots in Copilot Studio for the workflows Microsoft's default experience doesn't cover.
Custom plugins and connectors : Let Copilot query your CRM, ERP, or ticketing system directly from a Microsoft 365 conversation, instead of a user switching apps to find the answer.
Org-specific copilots in Copilot Studio : Purpose-built copilots scoped to a specific team or process, not a general-purpose assistant.
Grounded in SharePoint and Dataverse : Copilot answers from your actual internal documents and business data, not just public web results.
Data boundaries enforced, not assumed : Copilot only surfaces what a user's existing Microsoft 365 permissions already allow, we configure and test this explicitly.
Governance and usage oversight : Admin controls, usage policies, and audit visibility are set up from rollout, so IT has visibility into what Copilot is being asked and accessing.
RAG & Enterprise Knowledge
An LLM on its own doesn't know your product catalog, your pricing rules, or last week's policy change. Retrieval-augmented generation fixes that by retrieving the relevant piece of your actual data before the model answers, grounding the response instead of letting it guess.
Chunking strategy that preserves meaning : Documents are split in ways that keep context intact, instead of arbitrary fixed-length cuts that split a table or a clause mid-sentence.
Embeddings tuned to your content : We pick and tune the embedding model based on your domain, technical documentation, legal text, and product data don't retrieve well with the same defaults.
Hybrid search, not just semantic : Keyword and semantic search run together, so an exact product code or error message still gets found even when vector similarity alone would miss it.
Grounded answers over confident guesses : The model is constrained to answer from retrieved content, and told to say when it doesn't know, instead of filling gaps with a plausible-sounding hallucination.
Evaluation that catches drift : We test retrieval quality against real queries on an ongoing basis, so accuracy is tracked and tuned instead of assumed to stay good after launch.
AI Workflow Automation
Most workflows aren't slow because a step is hard, they're slow because someone has to read a document, make a judgment call, and re-type the result into another system. We combine LLM reasoning with deterministic steps, approvals, data lookups, validations, so the parts that need to be exact stay exact, and the parts that need judgment stop waiting on a person's queue.
Document and request understanding : The AI reads incoming invoices, forms, emails, or tickets and extracts what matters, amounts, dates, intent, priority.
Deterministic steps where it matters : Approval thresholds, validation rules, and required fields are enforced in code, the AI decides what needs review, not whether a rule gets followed.
Routing without a human dispatcher : Requests get sent to the right queue, team, or system automatically based on content and priority.
Cross-system handoffs without copy-paste : Data flows directly between the systems involved, CRM, ERP, ticketing, email, instead of a person moving it by hand between tabs.
Exception handling built in : Low-confidence or unusual cases get flagged for a person automatically, so the workflow degrades gracefully instead of silently doing the wrong thing.
Not sure where AI would create the most value in your business? Let's assess the opportunity together.
Microsoft AI Solutions FAQs
Common questions about AI agents, Copilot integration, RAG, and AI workflow automation on the Microsoft stack.
What AI and machine learning services does Akantik offer?
Akantik offers comprehensive AI services:
- Chatbot and conversational AI development
- AI agent development and workflow automation
- Microsoft Copilot integration
- RAG for grounded, accurate answers
- Custom models with ML.NET, Azure AI, and OpenAI
What is an AI agent and how can it help my business?
An AI agent is an autonomous, goal-driven software system that perceives its environment, processes information, and takes actions to complete tasks, improving efficiency and reducing operational costs.
What does Microsoft Copilot integration actually involve?
Copilot integration means connecting Microsoft 365 Copilot to your internal systems and data:
- Custom plugins and connectors to line-of-business systems
- Copilot Studio agents for org-specific workflows
- Grounding in SharePoint and Dataverse data
What is retrieval-augmented generation (RAG) and how does it reduce hallucination?
RAG retrieves relevant pieces of your own data before an LLM generates a response, grounding the answer in real content instead of relying purely on training data, which significantly reduces fabricated or inaccurate responses.
How is AI workflow automation different from traditional RPA?
Traditional RPA follows rigid, rule-based scripts that break when a process changes slightly.
AI workflow automation uses language models to understand intent and content, adapting to variation instead of failing outside a predefined pattern.
Can AI agents and Copilot integrations connect to my existing enterprise systems?
Yes, Akantik builds AI agents and Copilot connectors that integrate seamlessly with CRMs, ERPs, databases, APIs, and other enterprise systems for cross-system workflow automation.