AI agents, automation, and intelligent systems that ship to production.
117 services across 13 capability groups covering AI agents, RAG, voice AI, chatbots, RPA, and document automation for UK, US, Canada, and Australia.
Why AI & Automation?
We build AI and automation systems that go live in production, not demos that die on a slide deck. Our team ships AI agents, retrieval-augmented generation, voice AI, chatbots, RPA, document processing, and workflow automation for companies that have a real use case and need it running reliably in weeks, not quarters.
Clients hire us when an internal prototype stalls at 80 percent quality, when they need guardrails and evaluation frameworks to trust the output, or when they want to embed AI into an existing product without rebuilding from scratch. We work with OpenAI, Anthropic, Google, open-source models, and the tooling ecosystem around them.
What we will not do is ship without evaluation. Every system we build includes an eval set, monitoring, fallback logic, and human-in-the-loop escalation paths so you can measure quality, catch regressions, and trust the system in front of real users.
What we cover
Drill into a group to see the specific services inside.
AI Agents
Autonomous agents that research, decide, and act across your business workflows with guardrails.
RAG & Knowledge Systems
Retrieval-augmented generation systems that ground responses in your proprietary data.
Voice AI
Voice agents for inbound and outbound calls, IVR replacement, and real-time voice interfaces.
Chatbots & Conversational AI
Customer-facing chatbots with intent routing, context retention, and seamless human handoff.
RPA & Process Automation
Robotic process automation for repetitive tasks across legacy systems and manual workflows.
Document Processing
Intelligent document extraction, classification, and processing for invoices, contracts, and forms.
Workflow Automation
End-to-end workflow orchestration connecting your tools, data, and decision logic.
AI-Powered Analytics
Predictive models, anomaly detection, and natural language querying across your data.
ML Ops & Infrastructure
Model deployment, monitoring, versioning, and scaling infrastructure for production AI systems.
Computer Vision
Image recognition, video analysis, quality inspection, and visual search applications.
NLP & Text Intelligence
Sentiment analysis, entity extraction, summarization, and language understanding at scale.
AI Strategy & Consulting
Use-case identification, ROI modeling, vendor evaluation, and AI roadmap development.
AI Safety & Governance
Evaluation frameworks, bias testing, compliance documentation, and responsible AI practices.
Why teams choose Genvora for AI & automation
Production, not prototypes
We build systems that run in production with monitoring, fallbacks, and SLAs, not demos that die after the pitch.
Evaluation-first development
Every system ships with an eval set, regression tests, and quality metrics before going live with real users.
Model-agnostic delivery
We work with OpenAI, Anthropic, Google, open-source, and fine-tuned models. We pick what fits, not what is trendy.
Human-in-the-loop by default
Escalation paths, confidence thresholds, and human review steps built in so edge cases get caught.
Embedded in your product
We integrate AI into your existing stack rather than shipping a standalone tool that creates another silo.
Measured ROI
Every engagement starts with a baseline and ends with before/after metrics your CFO can understand.
How we engage
Discovery & use-case validation
We assess your use case, data readiness, and integration points to confirm AI is the right solution.
Scope & architecture
We define the technical approach, model selection, eval criteria, and timeline before writing code.
Build & evaluate
We build iteratively with weekly eval checkpoints, testing against your edge cases and quality bar.
Deploy & monitor
We deploy with monitoring, alerting, and fallback logic so the system is observable from day one.
Optimize & expand
We run monthly reviews against quality metrics and expand capabilities as the system proves value.
FAQ
Questions we hear most
It depends on the use case. RAG systems need proprietary data. Agent workflows often work with existing APIs and tools. We assess during discovery.
OpenAI GPT-4, Anthropic Claude, Google Gemini, Mistral, Llama, and fine-tuned open-source models. We recommend based on cost, latency, and quality tradeoffs.
Simple automations ship in two to four weeks. Complex agent systems with custom evaluation take six to twelve weeks depending on scope.
Yes. We audit existing systems, build proper eval sets, identify failure modes, and ship targeted improvements.
Guardrails, output filtering, confidence thresholds, human escalation paths, and documented evaluation frameworks are standard on every build.
Ready to ship AI that works?
We will assess your use case and define the right approach in a 30-minute call.