Where the engine has been put to work.

A fintech platform, embedding the control layer

AI Governance · Risk · Enterprise-ready

A fintech platform embedded Swiftward as a white-label control layer to clear the enterprise-readiness bar its corporate buyers demand: sanctions and KYC checks, transaction limits, human review for flagged activity, and a full audit trail, on its own infrastructure and stood up in weeks rather than the quarters a build would take.

Source-code leak prevention for a large financial institution

AI Governance

A large financial institution with thousands of developers needed to stop proprietary source code, and other sensitive data, from leaking into AI coding tools. The rare and genuinely hard piece was recognizing their own source code, and we built that detector. How it works.

An autonomous trading-agent harness, fully governed

AI Governance · Risk

We built and ran a working harness of four autonomous trading agents behind Swiftward. They read the open web, executed code, and made trading decisions - exposed on two fronts at once. For security, each agent was jailed behind the LLM, MCP, and network gateways, so a manipulated headline or a poisoned page could not turn into an unauthorized tool call, an exfiltration, or code reaching the open internet. For risk, every trade was checked against thresholds and counters - position and notional limits, velocity - by the same engine. Every decision landed in a tamper-evident trace. Real autonomous agents doing real, risky work, not a slide.

Working with design partners

Pilots are underway with design partners. We name a partner only with their written consent. When you book a demo, we work through your own use case and show how the engine would handle it.