From enterprise copilots and voice agents to document intelligence, automation and predictive models, Orion designs, builds and operates AI solutions around your data, workflows and business goals.
Orion starts with the business problem, identifies where AI can create measurable value, and then selects the right models, platforms and integration approach.
Build more intelligent customer and employee experiences.
Reduce manual work and process complex information faster.
Use proprietary data to improve decisions and operational performance.
Build grounded AI assistants and knowledge experiences that work with approved business data and existing enterprise systems.
Integration context. Connects to the document stores, intranets and line-of-business systems your teams already use, respecting existing permissions.
Discuss a generative AI use caseAn AI system that reads incoming emails and their attachments, understands intent and triggers the right downstream action — removing manual inbox triage and data entry.
Deploy chat and voice experiences that understand intent, answer questions, complete tasks and connect conversations to operational systems.
Integration context. Sits between your telephony or chat channels and your CRM, calendar and ticketing systems, with clean handoff to human teams.
Explore conversational AI deliveryA multi-agent AI reception platform using seven specialised agents, with streaming responses, early intent detection and interruption handling for natural conversations.
Automate multi-step business processes using controlled AI actions, system integrations and human approval points.
Integration context. Acts across your existing APIs and back-office systems, with every action logged and reversible rather than fire-and-forget.
Identify an automation opportunityAutomated purchase-order acknowledgement — tracking, reviewing and reconciling documents against the ERP, with exceptions routed for human approval.
Extract, classify and understand information from documents, images and video, with human review where confidence is insufficient.
Integration context. Feeds structured output straight into your ERP, DMS or line-of-business system, with a review queue for anything below threshold.
Discuss a document or vision workflowExtraction and classification of measurements and specifications from construction drawings, with confidence scoring and a review queue below threshold.
Select, adapt, evaluate and deploy models around specialised business knowledge, proprietary data and operational requirements.
Integration context. Deployed into your cloud account or a private environment, versioned and monitored alongside the rest of your platform.
Evaluate your custom-model requirementA life-coaching model trained on more than 500 coaching e-books and structured around the International Coaching Federation framework.
Turn historical and operational data into forecasting, recommendation, anomaly-detection and decision-support systems.
Integration context. Surfaces predictions inside the dashboards and applications your teams already work in, not a separate analytics silo.
Discuss a predictive analytics use caseForecasting and anomaly detection over historical operational data, surfaced inside existing dashboards to support pricing and inventory decisions.
Clarify the business problem, users, systems and success criteria.
Review data, integrations, risks and technical feasibility.
Select the architecture, models, guardrails and human controls.
Develop the AI capability and connect it to existing systems.
Test quality, security, usability and business outcomes.
Deploy, monitor, improve and support the production system.
An AI system that reads incoming emails and their attached documents, understands intent, and triggers the right downstream actions automatically — removing manual inbox triage and data entry.
A multi-agent AI reception and automation platform using 7 specialized agents working together. Streaming responses, early intent detection, and interruption handling deliver natural, human-like conversations, while async processing, response caching, and conversation checkpoints keep interactions seamless and efficient.
AI voice assistant automating repetitive tasks and boosting inbound/outbound call volume across healthcare, retail and recruitment — qualifying and converting leads 24/7.
A life-coaching AI trained on more than 500 coaching e-books and built around the International Coaching Federation framework — guiding users through structured, coach-quality conversations.
Computer vision that replaces manual, error-prone review of building plans — automatically identifying doors and windows to speed up estimation.
Automated PO acknowledgement — tracking, reviewing, and matching purchase orders across 100+ divisions, eliminating repetitive manual processing.
From architecture through production, Orion combines specialist AI engineering with accountable delivery and long-term technical oversight.
Specialists assigned around the actual use case — not a generic development pool.
A named delivery lead owns planning, communication, quality and escalation.
Systems designed for monitoring, maintainability, security and integration.
Security, access control and responsible data handling considered throughout implementation.
A modern, production-grade stack spanning foundation models, machine learning, cloud infrastructure, APIs and data systems.
Scope, timelines, data handling and what happens after deployment. Anything else, ask us directly.
Talk to our teamWe start with a discovery session on the business problem, the data available and the systems involved. Some problems are better solved with conventional software or process change, and we will say so — a short assessment is cheaper than an AI build that does not fit.
Yes, and most of our work is exactly that. We add capability to systems already in production, connecting through existing APIs, data stores and authentication rather than asking you to replatform.
Often not. Retrieval-based approaches work with your existing documents and records without training a model. Custom models need more, and part of the assessment is telling you honestly whether your data supports the outcome you want.
Access control, data handling and audit requirements are addressed during design rather than added later. We work inside your cloud accounts and identity provider where you prefer, and sign your NDA and data-processing terms before any access is granted.
Yes. We deliver on AWS, Azure and Google Cloud, and work with commercial model providers and approved open-source models. Platform choice follows your existing estate, procurement position and data-residency requirements.
A prototype becomes a product through evaluation, guardrails, monitoring, integration and operational ownership. We assess what exists, identify the gaps against production requirements, and sequence the work needed to close them.
Yes. Production AI needs quality monitoring, drift detection, cost tracking and a route for handling failures. Ongoing support is scoped per engagement, from responsive support to a fully operated service.
Discovery and assessment typically run two to four weeks. A first production capability commonly lands inside a quarter, depending on integration complexity, data readiness and approval cycles. We scope in phases so value arrives before the full programme completes.
Tell us what you want to improve, the systems and data involved, and where you are in the journey.
Delivering innovative software & AI solutions that empower businesses to thrive in an ever-changing world.
Company
Hire Developers
Products
© 2026 Orion eSolutions. All Rights Reserved.
Ex-McKinsey & a
seasoned IT entrepreneur
