Enterprise technology
We build for software companies putting AI inside their own product, and for the engineering estates that technology-led organizations already run.
A technology company that buys AI engineering is an unusual client, because it can already build. The question is rarely whether your engineers are good. It is whether a probabilistic feature can go in front of paying customers, be supported when it answers badly, and survive the security review your largest accounts will run on it. That work sits beside the software your team already ships well.
What changes when AI is in the product
Shipping AI inside a product breaks the assumptions your release process was built on. A deterministic feature is either right or it is a bug. A model-backed feature is right most of the time, and the interesting question is what happens in the rest. That means acceptance criteria written as evaluations rather than test cases, a regression suite that runs against prompt and model changes the way tests run against code, and a support path for the answer that was wrong in front of a customer. We build those alongside the feature, not after it.
Your customers' security review is the gate
For a software vendor, the AI feature is not finished when it works. It is finished when your largest customer's security team accepts it. That review asks where data goes, what the model is allowed to see, how tenants stay separated, what is retained and what is logged. The founders build and operate security tooling that reports against SOC 2, ISO 27001, HIPAA and PCI-DSS, so we write those answers into the architecture rather than assembling them for a questionnaire afterwards. Isolation, retention and audit logging are harder to retrofit than to decide at the start.
The internal estate, not a greenfield
The other half of this sector is the estate you already run. Identity, CRM, ERP, data platforms, ticketing and the internal tools nobody has time to replace. AI that ignores that estate becomes another system to integrate later. We design against what is actually deployed, including the parts that are old, and we treat integration and observability as build scope rather than a follow-on phase. The founders run a network and security engineering firm today, working across multiple vendors in live operations, so multi-vendor reality is a starting assumption rather than a surprise.
What we can actually point to
The honest evidence for a technology buyer is software the founders designed, built and still operate. Antenna is an open-source multi-brand publishing and analytics platform where AI agents work the same tools people do. Redwipe is an attack-surface management platform for security teams. Perdais is a legal platform where candidates, attorneys and staff each see only what their role allows. Zilk is an engineering firm running its own network and security products in live operations. These are our own ventures, not client engagements, and we present them that way.
What we build for technology companies
- The AI feature itself, built into your product rather than bolted beside it: retrieval, agents, copilots or decision logic, living in your codebase and your release process.
- An evaluation suite that serves as the acceptance criteria for the feature, and a regression harness that runs on every prompt and model change.
- The data and serving layer underneath, including tenant isolation, retrieval indexes and the pipelines that keep them current.
- Security architecture written for your customers' review: access controls, data-handling decisions, retention rules and audit logging, documented so your team can answer a questionnaire without us in the room.
- Observability built for the people who carry the pager, showing what the feature is doing in production and where it is failing.
- Handover as a deliverable, with runbooks, documentation and working sessions so your own engineers own and extend the system.
What this is not
This is not a staffed sector practice. Caltor has no technology industry unit and no client names to show you in this sector, and we do not sell headcount into your engineering organization. Antenna, Redwipe, Perdais and Zilk are the founders' own ventures, presented here as our own work and never as client engagements.
Talk to a partner
If you are putting AI into a product your customers pay for, tell us what the feature has to do and where it has to survive.
