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AI agent and generative AI development

We build and run your AI agents and generative AI applications

Hand us the project. We design it, build it in your repository, connect it to your systems and run it in production, or hand it to your team. You keep the code, the data, the keys and the final say.

  • Code in your repo
  • Human approval gates
  • Self-hosted or managed

What we build for you

Agents, generative AI apps and the integrations that make them useful

Most AI projects stall between the demo and production, usually on the integration and operations work. We take all of it on, so there is one team to hold to account.

Benefits of TenthMatrix AI agents

What you get when our agents do the work

Each benefit maps to software we build and run ourselves, so you can inspect it before you sign anything.

  • A person approves what matters

    Agents draft and prepare. Anything that sends, spends or deletes waits for a named person.

    See Jobshout
  • Self-hosted or managed

    Run the agents in your own cloud or data centre, or have us run them. The code is the same either way.

    Engagement models
  • Your data and keys stay with you

    Data stays in your systems and model keys stay in your secrets store. Pick the model provider, or host an open-weight model yourself.

    Security and IP
  • Secrets isolated per agent

    WSL Vault issues short-lived, scoped credentials, encrypted per tenant and recorded in a tamper-evident audit log.

    See WSL Vault
  • Releases gated on health

    Ring Promoter moves each change from int to prod only when health checks pass, and rolls back when they fail.

    See Ring Promoter
  • Security at the edge

    WSL Proxy puts an API gateway, WAF rules and rate limits in front of the agent and the tools it calls.

    See WSL Proxy
  • Cost and behaviour you can see

    A trace for every run, cost and latency per agent, and alerts when either drifts.

    How we measure
  • Built by a team that runs agents

    Our own agents run in production on this stack. We publish how they work, including what broke.

    Read the articles

How outsourcing works

Discovery, pilot, build, then run or hand over

Each stage ends with something you keep, even if you stop there.

  1. 01 / 04

    Discovery

    We pick one job, the systems it touches and who checks the result, and write down what the agent must never do. You get a written scope and a fixed quote for the pilot.

  2. 02 / 04

    Pilot

    The smallest version that does the real job on real data, behind approval gates, measured against the scope. Then a go, change or stop recommendation.

  3. 03 / 04

    Build

    Production code, integrations, secrets, guardrails, tests and a release path, all in your repository. You can read every prompt, trace and test.

  4. 04 / 04

    Run or hand over

    We operate it with monitoring, cost reports and a regular review, or hand it to your team with runbooks and training.

Engagement models

Four ways to work with us

Choose by how clear the job is and how much you want to own at the end.

Proof

Software we build and run ourselves

Client agents run on the same products we use in production. Each one started as something our own agents needed.

  • Ring Promoter

    CI/CD control plane

    Promotes every release through int, test, acc and prod rings. Health gates decide, and failed checks roll back on their own.

  • WSL Proxy

    API gateway · CDN · WAF

    Sits in front of your origins with live configuration, an edge cache and WAF rules. An MCP gateway for agents is on the roadmap.

  • Open source

    WSL Vault

    Secrets manager

    Envelope encryption with a key hierarchy per tenant, dynamic leases and a tamper-evident audit log. Steal the server, not the secrets.

  • Open source

    Jobshout

    Agent orchestration

    Specialist agents that work in Gmail, GitHub and live sites, stream every step and stop for your approval before anything goes out.

  • Research

    Jev

    Decision-layer research

    Our independent series and benchmark lab on fast decision models, agent harnesses, routing and the cost of inference.

  • Nebula family

    NebulaDB · NebulaDNS · NebulaCR · NebulaCB

    Rust infrastructure for agent workloads, from NebulaDB, a database with vector search and streaming RAG, to NebulaDNS, authoritative DNS with Prometheus metrics.

Writing

Latest from the team

Engineering notes, long-form technical articles and the Jev insights series.

Need the hardware?

GPU workstations and clusters live at Workstation

Our sister company sizes, builds and supports the machines that run private models. Tell them what you want to run and they will spec it.

Visit Workstation

Start a project

Tell us the job. We'll scope the build.

Send the task, the systems it touches and who checks the result. Within one working day an engineer replies with what we would build, what it should not do and how we would prove it.