Your portfolio is more advanced than the average AI vendor's roadmap.
We design and ship production AI — autonomous agents, MCP integrations that add AI to the software you already run, enterprise knowledge assistants (RAG), GenAI apps and intelligent automation — for businesses and governments. Then we stay on-site until your team is actually using it.
Gartner expects 40% of enterprise apps to embed task-specific AI agents in 2026 — yet most AI projects stall. The build isn't usually the problem. Adoption is.
Impressive demos that never reach production or real users.
Software delivered, then abandoned because no one drove adoption.
No explainability, no audit trail, no governance.
"Remote AMC + quarterly visits" the moment support is needed.
Production AI for 2026 — agents, MCP integrations, RAG assistants and intelligent automation, each with real proof
Autonomous agents that execute multi-step workflows by voice or chat. Proof: our GenAI voice-and-chat PMS — "show my tasks", "mark task 100 complete" — built on Flutter, Node.js and Gemini.
Give your existing ERP, CRM or app an AI layer using the Model Context Protocol — AI assistants securely read and act on your live business data without ripping out what you already run. Proof: MCP layers shipped into live ERP projects including a real-estate ERP.
Secure assistants that answer from your own documents with role-based access and citations. Proof: JB Helper Bot — RAG with department and designation-level permissions, Milvus + MongoDB.
LLM-powered products, copilots and content systems integrated into your existing stack. From customer-facing tools to internal productivity apps built on the latest foundation models.
RPA + AI for back-office workflows and fully automated, AI-generated reporting. Proof: an AI-based Attendance Management system and an AI-driven HRMS with automated reporting.
Image and video AI for security, monitoring and document processing. Proof: a Visitor Management System for a government organisation in Maharashtra — mobile + tablet apps with AI anomaly detection and automated AI reporting.
Forecasting, classification and data-driven decisioning. Custom ML models for customer behaviour, demand planning and operational efficiency built on your own data.
Opportunity assessment, ROI modelling, and a prioritised build plan. We identify the highest-impact AI use cases in your business and create a staged roadmap your leadership can act on.
Other vendors deliver and disappear. We embed with your team after go-live and measure one number most vendors won't: the 6-month utilisation rate. If your people aren't using the system, it isn't done.
We design and ship production AI — agents, RAG assistants, automations — scoped to your real business outcomes and built on your actual data.
We stay on-site after go-live, working alongside your team to integrate the system into daily workflows and resolve friction as it appears.
We track the 6-month utilisation rate. Adoption is the finish line — not go-live. We don't close the engagement until your people are genuinely using the system.
Build → Embed → Adopt. We don't leave until utilisation targets are met.
Most vendors selling "AI transformation" want to rebuild what you already run. We don't. Using the Model Context Protocol (MCP) — the emerging standard for connecting AI to live business systems — we add an intelligent agent layer on top of the ERP, CRM or software you already use.
Why now: Gartner expects 40% of enterprise apps to embed task-specific AI agents in 2026. MCP is how that happens without throwing away the systems you've already paid for.
Who it's for: any business sitting on an ERP or CRM that works but feels manual — the data is there, but getting to it takes clicks, exports and people.
"You don't need a new system. You need your current one to think."
Natural language over your live data
Your team asks "which AMC contracts expire this month?" or "create a quotation for this client" — and the system answers and acts on your real, live data.
No rip-and-replace
No data migration, no six-month re-platforming project. Your existing software keeps running; the AI sits on top and works through it.
Proven delivery
We've shipped MCP layers into live ERP projects — including a real-estate ERP where the client's in-ERP services were exposed to AI assistants via MCP.
Cutting-edge frameworks and tools for robust AI solutions
Proven methodology for successful AI adoption — including on-site embedding after go-live
We analyse your business processes, data landscape, and strategic goals to identify high-impact AI opportunities and define success metrics.
Develop a comprehensive AI roadmap with prioritised use cases, resource requirements, timelines, and ROI projections for stakeholder alignment.
Clean, label, and engineer features from your data. Establish data pipelines and quality assurance processes for model training.
Build and train AI models using state-of-the-art algorithms. Iterative testing and validation ensure optimal performance and accuracy.
Deploy models to production environments with proper scaling, monitoring, and security. Seamless integration with your existing systems.
Continuous monitoring, retraining, and optimisation of AI models. Regular performance reviews and updates to maintain accuracy and relevance.
We stay on-site after go-live and track the 6-month utilisation rate. If your people aren't using the system, it isn't done — this step closes the gap most vendors leave open.
What makes us the right partner for your AI journey
We embed on-site after go-live and track the 6-month utilisation rate. Most vendors ship and leave — we stay until your team is actually using the system.
Agile delivery means a focused AI agent or RAG assistant ships in 4–8 weeks. We deliver working systems quickly with iterative improvements.
Role-based access, citations and audit trails, encryption and access controls. Governance and explainability are built into delivery — not bolted on afterwards.
We've shipped AI across healthcare, finance, government, manufacturing and logistics. Industry-specific knowledge means faster scoping and better outcomes.
We work closely with your team so they can maintain and scale AI solutions independently. Every engagement ends with your people owning what we built together.
Every AI project is scoped with measurable business outcomes. We track KPIs and demonstrate clear value at every milestone — not just at go-live.
Everything you need to know about our AI services
Accucia builds AI agents, enterprise RAG knowledge assistants, generative-AI applications, intelligent process automation, predictive analytics and computer-vision solutions — from strategy through deployment and adoption.
We measure adoption, not just delivery. We embed on-site after go-live and track the 6-month utilisation rate, so the system is actually used — not shelved.
A focused agent or RAG assistant typically ships in 4–8 weeks; complex enterprise systems run 3–6 months from discovery to production.
Not always. Pre-trained models, transfer learning and RAG over your existing documents mean many projects start without a large labelled dataset.
Examples include a 75% cut in document search time (pharma RAG assistant) and a 60% drop in helpdesk queries (employee super-app). We define specific measurable metrics upfront for every engagement.
Yes — API-first integration with existing CRMs, ERPs, databases and custom apps. We can also add an AI agent layer to your existing software using the Model Context Protocol (MCP), so AI assistants can read and act on your live business data without replacing the system.
Role-based access, citations and audit trails, encryption and access controls — governance and explainability are built into delivery, not added as an afterthought.
Discover our AI-powered solutions and automation implementations
Let's discuss how AI can transform your business operations and drive measurable results. Book a 15-minute discovery call — no commitment required.
