Enterprise AI, engineered for production

Repetitive work that moves between systems and follows rules most of the time, such as inbox triage, invoice and claims processing, customer onboarding, ticket routing and KYC file assembly. Work that needs judgement on every case suits a copilot that drafts the work and lets a person decide.

A two-week discovery scores each candidate on value, effort and risk, and checks that the data it needs is available. You fund the top of the list, and we agree the KPIs with you before the build starts.

A working pilot on one workflow takes about six weeks after discovery. It runs on your real data with evaluations, guardrails and monitoring in place, so it can move to production without a rebuild.

It depends on the workflow, the systems involved and how much the agent does on its own, and you get a written estimate before any work starts. There are three ways to work with us: a dedicated AI team billed monthly, a fixed-price project for a defined scope such as the two-week discovery or a six-week pilot, or hourly help for smaller jobs such as reviewing an existing agent or its prompts, billed only for the hours used.

CRMs, ERPs, email, ticketing tools, WhatsApp and web chat, data warehouses and your internal APIs. Each agent gets its own role-based permissions, scoped to the job it does.

The one your data rules, cloud and workload call for. OpenAI suits voice, vision and customer-facing agents, Claude suits long, regulated documents and agent orchestration, and Azure OpenAI keeps models inside your own tenant and region. We build a model layer so you can switch provider later.

Answers are grounded in your own content and cite their sources. Each agent can only do what its permissions allow, and actions above a set threshold, such as a refund or a price change, wait for a person to approve them. Evaluation suites run against your real examples before every release.

Yes. We design bilingual conversations, including right-to-left layouts, and test answer quality in both languages before launch.

Agents only see the data their task needs. We can deploy privately or inside your own Azure tenant, and every action is logged. Your data is not used to train shared models unless you agree in writing.

We design the hosting, data flows and access controls around the standards you work under, such as GDPR, HIPAA or SOC 2. Your risk and audit teams get role-based access and a complete action log to review before they approve it.

Each task uses the smallest model that meets the quality bar, common requests are cached, and a usage dashboard shows spend per agent, so costs stay predictable as usage grows.

You own the code, prompts and evaluation suites, delivered in your repositories with documentation. Your team can run it, or we can monitor and improve it under a support retainer with on-call runbooks.