Services · forward-deployed engineering
We build with your team, measure the system across every layer, and keep it current through every model change. Start with a fixed-scope review, sprint or design, or go straight to a build.
The system behind the AI product
Where are you starting?
The first engagement depends on where your agents are today. Every one of them runs on the Harness Method.
Build
Add an AI feature, connect it to your systems, or build an agent workflow, measured from the first week.
Forward-deployed build · initial three-month engagementEvaluate
Find where the time and money go, score the agent on five measures and fix what matters first.
Harness Review · two to three weeksRun
Monitor agent behavior, respond to incidents, improve the system and evaluate model changes against your own cases.
Forward-deployed operations with Harness Watch · monthlyDesign
Choose the workflow worth automating, compare the ways to do it and prove a first version.
Harness Design · three weeksHow to engage
The forward-deployed build is the core engagement, and Harness Watch keeps us on after launch. The fixed-scope starts and the advisory work stand on their own or lead into a build.
Forward-deployed engineering
Engineers embed with your team, build the system, and stay on monthly to run it.
The core engagement
Initial three-month engagement
Forward-deployed engineers embed with your team and build the agent platform, AI product or the systems behind it, measured with the Harness Method from the first week. Scope, milestones and acceptance criteria are agreed before work starts.
What the scope includes
Working software, a scorecard on quality, speed, cost, control and drift, the harness your engineers keep using, release gates, runbooks, and a handoff your team runs with.
The proposal defines the workstreams, personnel, milestones, acceptance criteria, dependencies, tooling rights and transition. The work is finished when your team can ship the next model change through the gate.
After launch
Monthly retainer, with Harness Watch
After launch, we stay on to run Harness Watch: a verdict on each relevant model release, a monthly scorecard, incident response and ongoing improvements.
How Harness Watch worksFixed-scope starts
A defined question, a fixed scope and a fixed price, with the evidence left in your repository.
Two to three weeks · fixed price
An AI agent audit across every layer: where the time and money go, a scorecard on five measures and a prioritized fix plan.
Outputs: Harness Map, Scorecard, model and settings comparison, control findings, fix plan, and the test runner in your repository.
Explore the Harness ReviewFive working days · four a month
Five to 25 of your agent's cases on your current model and its replacement: what a model change does to your agent before your users see it.
Outputs: A one-page scorecard on quality, speed, cost, control and drift, with every observed regression listed.
Explore the Next-Model CheckThree weeks · fixed price
Choose the workflow worth automating, compare the ways to do it and prove a first version before a larger build.
Outputs: Workflow choice, options compared, a one-page Harness Spec, a test set, a scored prototype and a build plan.
Explore the Harness DesignAdvisory
Technical judgment for investment, acquisition and leadership decisions.
Two to four weeks
Evidence for an investment, acquisition or major platform commitment, including the real state of an agent-built codebase.
Outputs: Evidence-backed findings, material risks, integration and remediation plan, and a readout for the deal team.
Discuss diligenceInitial three-month term
A senior technical counterpart for architecture, agent adoption and the decisions your board and investors ask about.
Outputs: Architecture decisions, agent-adoption plan, delivery reviews, and leadership and board readouts.
Explore this optionStart with a fixed-scope review, sprint or design, or go straight to a build. Timing, access and acceptance are set in the proposal before work starts.
AI-Native SaaS / selected work
Backend AI, API and infrastructure engineering, from architecture through launch.
Read case studyAgent platform engineering
Engineering capabilities
The product and agent layer: workflow architecture, MCP tools, scoped authorization, approval interfaces and human escalation.
Explore capabilityAcceptance evidence for the release: eval harnesses, retrieval quality, traceability, operational limits and recovery paths.
Explore capabilityThe systems underneath: identity, cloud environments, data architecture, secure integration and operational ownership.
Explore capabilityHow we build
Harness engineering is how we prepare the context, tools, permissions and feedback around an agent. The Harness Method adds the measures, the review and the release ownership.
Every change runs through these gates. Your team receives the project guidance, checks and operating workflows alongside the software, so the speed carries over to your own engineers.
The Harness MethodThe software construction loop
Define the outcome, acceptance criteria and exclusions. Prepare the repository context and allowed tools.
Start a conversation
Tell us what you’re building, what is getting in the way, and the outcome you need.