Every action authorized
Per-caller, per-resource checks on every tool call, with human approval wherever money or customer records move.
For fintech and financial services
Built with the authorization, safe retries and audit trail financial systems require, so an agent can read accounts, prepare actions and work alongside your operations team.
What we solve
Per-caller, per-resource checks on every tool call, with human approval wherever money or customer records move.
Idempotent tool actions, so a timeout or a repeated request cannot execute the same operation twice.
Traces that connect the request, the model's reasoning, the tool call and the approval behind every outcome.
Proof
We built the agent platform behind a product used by large enterprises and a unicorn startup: 50+ MCP tools, semantic search and model integrations with Anthropic, OpenAI and Google.
AI-Native SaaS / selected work
Backend AI, API and infrastructure engineering, from architecture through launch.
Read case studyAgent platform engineering
How we engage
Build with a forward-deployed team, keep it current with Harness Watch, or start with a Harness Review before you expand what the agent can do.
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.
You get: 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.
Explore this optionMonthly 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.
You get: Release verdicts, a monthly scorecard, a quarterly autonomy review, incident response, improvements and a leadership readout.
How Harness Watch worksTwo 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.
You get: Harness Map, Scorecard, model and settings comparison, control findings, fix plan, and the test runner in your repository.
Explore this optionOr start where your agents are today
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 weeksGo deeper
Start a conversation
Tell us what you’re building, what is getting in the way, and the outcome you need.