Technology ecosystem · Applied expertise
Numezis works hands-on with the enterprise workspaces, coding agents and model platforms reshaping knowledge work and software delivery. We configure them, connect them to real systems, test their limits and build the controls required for production.
Built by Numezis
Kletron is our complete agent and multi-agent work system. Building and operating it gives us direct evidence about orchestration, permissions, evaluation, human review, cost and reliability — the same production questions our clients face.
Platforms we work with
A platform is valuable only when it fits the workflow, data boundary and operating model. Our experience spans deployment, secure configuration, integrations, evaluation and day-to-day use — not a feature checklist.
Anthropic
Knowledge work · software engineering
Enterprise adoption and agentic coding workflows designed around permissions, context, tools and review.
OpenAI
Enterprise work · agentic software delivery
Governed workspace adoption and engineering systems that turn Codex into a controlled delivery capability.
Knowledge work · enterprise agents
Permissions-aware enterprise search, multimodal assistance and agent platforms connected to organizational data and workflows.
Mistral AI
Enterprise assistants · sovereign AI
The unified Mistral experience for work, code and chat, combined with model platforms and hybrid deployment choices.
NVIDIA
Inference · AI infrastructure
Production AI infrastructure for optimized model serving across cloud, data center and edge environments.
Moonshot AI
Research · local agent workflows
Agent workflows across files, browsers and recurring work, evaluated with explicit permission and data boundaries.
Cloud AI platforms
Model access is only one layer. We design the identity, data, network, agent runtime, evaluation, security and operations required to make Microsoft Azure, Google Cloud and AWS dependable enterprise AI platforms.
Architecture-first
We also engineer with Kletron, open-weight models and cloud, local or self-hosted deployment patterns. The right system can combine products when the architecture makes the boundaries and responsibilities explicit.
Numezis technology for controlled, integrated enterprise AI workflows.
Selected when control, economics or specialization justify lifecycle ownership.
Connections to identities, data, tools and systems where operational work happens.
Deployment follows risk, performance, sovereignty and operating capacity.
Operational depth
We turn product familiarity into a repeatable enterprise capability. The work starts before rollout and continues after the first successful task.
Benchmark products on representative workflows, data and failure modes.
EVAL SET / DECISION RECORDSet workspaces, identities, permissions, policies, retention and review paths.
CONTROL BASELINEConnect APIs, MCP servers, source systems, repositories and observability.
TRUST BOUNDARIESTest attacks and failures, capture evidence and establish incident ownership.
ASSURANCE / EVIDENCEInstrument adoption, quality, cost and workflow value before expansion.
VALUE / OPERATIONSOpenClaw · NVIDIA NemoClaw
We deploy OpenClaw inside explicit trust boundaries and apply NemoClaw and NVIDIA OpenShell patterns where sandbox isolation, network policy, filesystem restrictions and managed inference are required.
Explore secure OpenClaw deploymentTechnology relationships
Numezis is progressing partnership conversations with most of the providers represented on this page. Our implementation experience already exists; formal partner status remains subject to each provider’s approval and public confirmation.
Until a relationship is formally approved and announced, the logos above identify technologies we implement. They do not imply an announced partnership, certification or endorsement.
Selection discipline
Every recommendation is recorded against six criteria and includes the conditions that would trigger a review or exit.
Residency, retention, training use, context and access.
Identity, APIs, MCP, repositories and business systems.
Isolation, permissions, audit, supply chain and response.
Quality, latency and reliability on the real workflow.
Licenses, inference, engineering, operations and change.
Portability of data, evals, agents and integrations.
Bring us the workflow, constraints and evidence. We will make the tool decision explicit.