How We Deliver
Six stages. Proprietary. No experimentation. No guesswork. From problem definition to working agents in your environment — in 6–8 weeks.
Before we design anything, we understand everything. Our discovery process maps the business problem with precision — not at the level of "we want to use AI" but at the level of "this specific decision, made by this specific person, at this specific point in the workflow, is where value is lost."
We conduct structured stakeholder interviews, workflow archaeology sessions, and data landscape mapping. We identify what data exists, what context is missing, and what the organisational intelligence looks like that an agent would need to be effective.
With the problem understood, we architect the solution. This stage produces three key outputs: the Context Layer schema (what The Brain will contain and how it will be structured), the LLM selection rationale (which model for which task, and why), and the agent blueprint (what it will do, what decisions it will make, and where the human remains in the loop).
LLM selection is never a default. We evaluate against six dimensions per use case: accuracy, latency, cost per token, hallucination rate, integration complexity, and compliance readiness. The best model for your problem — not the most marketed one.
We build The Brain first. The Context Layer is constructed from the data sources, workflow logic, and institutional intelligence identified in discovery — structured into a knowledge graph that the agent will draw from at runtime. This is what separates OXEVA's agents from generic AI tools.
Agent engineering follows, with hallucination controls woven in throughout — not bolted on at the end. Our proprietary validation layers check every output against ground truth, flag anomalies, and route edge cases for human review before they surface to end users.
Most AI failures in enterprise are not dramatic — they are subtle hallucinations that erode trust over weeks. Our approach:
Deployment into your actual environment — not a sandbox, not a demo. We manage the change management process alongside technical deployment, ensuring the people who will work with the agent understand it, trust it, and know where they remain in control.
We treat deployment as the beginning of the relationship, not the end of the project. The first two weeks in production are the highest-learning period — we are on-site (or on-call) throughout.
Every OXEVA deployment ships with a live intelligence dashboard. Token-level consumption, output accuracy rates, processing volumes, error patterns, and direct mapping to business KPIs. You always know what your agent is doing and what it is costing — to the cent.
The observe stage is not passive monitoring. It generates the data that drives Brain enrichment, agent optimisation, and the roadmap for the next agent. Intelligence compounds over time.
An agent that works in one function becomes the proof point for the next. The Brain built for FP&A can be extended to inform the MIS Agent. The PMO Agent context feeds into Security Agent alerting. Intelligence built in one department compounds across the organisation.
Scale stage includes agent workforce management — a single-pane view of all deployed agents, a structured roadmap for new ones, and ongoing Brain enrichment as your organisation evolves. OXEVA retainers are built for this stage.
See the methodology in action
In two to four weeks, we run stages one and two with you. You get a full Context Layer scoping, agent blueprint, and ROI hypothesis — before any development begins.
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