AI that knows your business
Ekva connects your enterprise data, applications and AI models—so teams get grounded answers, automate workflows and control AI costs.
What changes with Ekva
Useful answers and actions across the systems you already run, with deliberate control over models and data.
Up to 70%
lower AI spend
Route routine work to efficient models and reserve premium models for tasks that need them, so spend tracks value.
Savings vary by model mix, workload and baseline; validate during your pilot.
Right model
for every task
Ekva matches each request to a model that fits its needs, balancing quality, speed and cost instead of one model for everything.
Your rules
on your data
Protect enterprise knowledge with access permissions, governance and data-handling policies configured for your deployment.
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connected layer
A single intelligence layer across your systems, knowledge and workflows, replacing scattered, disconnected chatbots.
As AI moves beyond pilots, disconnected systems leave each person's work in pieces. Without shared context, choosing the right model, carrying permissions across tools, and planning AI spend all get harder.
of respondents say AI is scaling across their enterprises, up from 38% a year earlier.
McKinsey (2026)forecast growth in worldwide AI spending in 2026, year over year.
Gartner (2026)of surveyed AI data decision-makers cited siloed or hard-to-integrate data as a preparation obstacle.
Cloudera / HBR Analytic Services (2026)Ekva bridges the gap between raw models and your business. By connecting data and applications, it adds context to each request and works within your existing permissions.
Unify structured data sources and draw relevant signals from the applications your teams use.
A context layer interprets the request and selects a suitable model for the task.
Ground answers in connected evidence while applying existing access rules.
One workflow, end to end
A finance leader asks one question. Here is how Ekva moves from scattered systems to an explained answer and a governed next step.
Receivables ageing from the ERP, account notes from the CRM, contract payment terms from the document store.
Only records the asking user is already allowed to see are assembled into context.
Routine extraction uses an efficient model; complex explanation uses a stronger one, within approved boundaries.
Each driver of the slowdown links back to the invoice, note or clause it came from.
Draft reminders for overdue accounts and a review task for disputed invoices.
Nothing is sent or updated until an authorised person reviews and approves it.
Illustrative workflow showing how the steps fit together. It is not a customer case or a live product screenshot; connected systems, models and approval rules are configured per deployment.
Ask a question. Get a report. Start or track a process. Ekva Voice brings your connected business to your phone, with the context to act and the choice to stay in control.
From finance and operations to sales and people teams, Ekva brings enterprise AI into the systems they already use — so everyone can ask, understand, and act with the right context.
Security and governance
Exact controls depend on your deployment architecture. We walk through them, and the evidence available, with your security and compliance teams before any pilot.
Requests are scoped to the permissions a user already holds in connected systems, configured per role and source.
Where data is processed depends on the architecture you choose. Any external model is used only after your team reviews and approves it.
Where the workflow supports it, answers reference the records used so people can check them.
Queries, model calls and actions can be logged for review. Retention and scope are set for your deployment.
Choose which models handle which tasks, balancing quality, cost and data-handling requirements.
Proposed actions can require sign-off by an authorised person before anything changes.
How a pilot works
Pick one business question or process with a clear owner, known systems and a baseline you already track.
Map the systems to connect, access rules, deployment boundary and any external models your team approves.
A defined group uses Ekva on real work, with human approval on every proposed action.
Compare answer quality, AI cost and business impact against the baseline, then decide whether to expand.
Whitepapers & Guides
A technical guide covering air-gapped architectures, model governance controls, and compliance documentation for BFSI, healthcare, and government AI deployments.
A CFO-ready framework for modelling AI TCO across cloud LLM APIs and private infrastructure. Includes scenario-based worksheets for your own usage and procurement assumptions.
A practical guide to mapping applicable governance expectations to platform controls and audit evidence. Written for GRC leads and compliance officers.
Explore deployment options for your environment. Data flows and delivery timelines depend on the architecture, integrations, and review requirements you select.
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