Engineering
Full-stack applications, agentic systems, and evaluation harnesses.
The engineering lane turns product or workflow context into usable software: interfaces, APIs, data models, integrations, AI controls, context systems, harnesses, and release paths.
Need help choosing the right route? Share the product, workflow, or AI system and we will map the safest next step.
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Full-stack application engineering
Why it matters
Build the workflow as usable software, not as another spreadsheet around the same problem.
What FoxTech does
We choose the app stack, data model, UI, API, and database around the service.
Client benefit
- The product is easier to test, release, monitor, and hand over.
Context engineering
Why it matters
AI and agentic systems need the right source-grounded context, tool boundaries, and review loop.
What FoxTech does
We design retrieval, memory, prompts, tool access, evidence capture, and context packs around the actual task.
Client benefit
- AI assistance becomes easier to inspect because inputs, constraints, and source evidence are visible.
Harness engineering
Why it matters
Prompts, agents, integrations, and workflow automation need repeatable tests before teams trust them.
What FoxTech does
We build evaluation harnesses with golden paths, failure cases, traces, review rubrics, and regression checks.
Client benefit
- Teams can see what works, what regressed, and what still needs human review.
Integrations and data
Why it matters
Connect the systems that already carry part of the service journey.
What FoxTech does
We link CRMs, booking tools, inboxes, spreadsheets, payment systems, portals, and APIs where useful.
Client benefit
- Duplicate entry drops and reporting becomes more reliable.
AI-assisted workflow
Why it matters
Use AI and agents where they speed up repetitive work without hiding judgement.
What FoxTech does
We add extraction, summaries, triage, routing, drafting, tool use, and reporting with review controls.
Client benefit
- Teams move faster while sensitive output stays accountable.
Cloud delivery
Why it matters
Production systems need release, monitoring, secrets, and support paths from the start.
What FoxTech does
We set up deployment, observability, health checks, rollback paths, and handover notes.
Client benefit
- Launch is controlled and support does not depend on guesswork.
Agentic and context engineering evidence
Fire protection field-service workflow
Why it matters
Paper-heavy field work needs structured handoffs between service desk, technicians, report review, billing, and audit history.
What FoxTech does
We mapped source forms into a role-based field-service MVP with digital questions, source references, work-order states, review steps, and deployment evidence.
Client benefit
- 29 source templates became 1,229 digital questions with 1,260 source references and 0 unmapped digital questions in the audit.
Sensitive product AI controls
Why it matters
Sensitive service products need access, auditability, continuity, privacy workflows, and careful AI boundaries before launch claims are made.
What FoxTech does
We mapped referral workflows, hosted operations evidence, approval blockers, and a disabled-by-default AI assistant model using permission-checked server-side tools.
Client benefit
- Governance and hosted baseline evidence stayed visible while final legal, controller, clinical, processor, production-auth, and AI-provider approvals remained explicit pending items.
Context-aware engineering agents
Why it matters
Coding agents need relevant project context, retrieval quality, and verification gates to avoid broad, risky edits.
What FoxTech does
We build GraphRAG/MCP-style context systems, specialist-agent workflows, sandboxed execution, retrieval evaluation, and review lanes around AI-assisted delivery.
Client benefit
- Agentic work becomes easier to inspect, verify, and hand over because context, tools, acceptance criteria, and evidence are separated.
AI-native delivery controls
Why it matters
Useful AI automation must stay bounded by roles, data sensitivity, operating rules, and human review.
What FoxTech does
We design AI features around tool permissions, no autonomous sensitive writes, audit trails, fallback paths, and release checks.
Client benefit
- Teams can adopt AI assistance with clearer operating boundaries instead of relying on unsupervised model output.