We design, build, and operate production-grade AI agents on top of OpenAI, Anthropic, Gemini and LiveKit. Voice, chat, multi-step task agents — every one ships with an eval harness, cost ceilings, and a route into your existing systems.
We use the same eval-first playbook across every surface — voice, chat, multi-step. The shape of the agent changes; the engineering doesn't.
LiveKit + Twilio front-ends with sub-second latency. Drop-in replacement for tier-1 call handling — turn-taking, barge-in, graceful handoff to a human when the agent isn't sure.
Inline assistants and standalone chat surfaces that retrieve from your data, write back to your systems, and cite their work. Embedded in your product or as a standalone surface.
LangGraph state machines for workflows with multiple turns, branches, and escalation paths. Predictable where you need it; flexible where you don't.
Every agent we ship comes with a CI-wired eval set built from your real cases. Regressions get caught at PR time, not by your customers in production.
Every engagement targets a live, evaluated agent in your stack — owned by your team when we walk away. No demos, no lock-in.
We sit with the people doing the work today — your product team, your end users, your operators. What does the workflow look like? Where does it break? Outputs: agent spec, success metrics, and a clear build/buy decision before any code is written.
An evaluated v0 against your real data — not a demo on slide deck. Run live queries, see real outputs, pressure-test before we commit to production hardening.
Function calls, retrieval pipelines, evaluation harness, fallbacks, audit logs, cost ceilings, role-based access. The system your platform can run in production from day one.
Documented system, trained team, full source code. From here: clean exit, or 3-month retainer at £8-12K/month for continuous AI development and weekly evals.
Below is what we've put in production in the last 18 months. The frameworks come and go — the engineering doesn't.
End-to-end voice agent for a children's education app — full AI conversation stack, character voice, content safety, age-appropriate guardrails. Currently live in the App Store. 9-month build, $100K engagement.
Built an AI-powered recruiting marketplace MVP from scratch for a UK founder — Next.js, LangGraph, GPT, candidate matching, full platform. Shipped on time and on budget in 12 weeks.
Not here? Email us at hello@futureproof.technology — we reply within one business day.
Most engagements ship a live, evaluated agent in four to six weeks. We don't ship demos — when an agent goes live, it's instrumented, eval-covered, and has a documented hand-off path to your team.
Whichever ships. We've put OpenAI, Anthropic, Gemini, Mistral, and self-hosted models into production in the last 18 months. We pick based on latency, cost, and accuracy on your eval set — not on vendor relationships.
We build it. Every engagement starts with a corpus of real cases pulled from your support inbox, ticket queue, or transcript archive. That corpus becomes the eval set, wired into CI, scored on every model bump.
Your team owns the system. We hand off code, tests, runbooks, the eval corpus, and a roadmap. Optionally we stay on retainer to run weekly evals and respond to regressions — but it's an option, not a lock-in.
Yes. Most agents we ship have function-calling into a CRM, EHR, dispatch system, or internal API. We use whatever you already have — REST, gRPC, queues, webhooks — and write thin adapters where we need to.
We default to your hosting (your AWS / GCP / Azure account). We've shipped HIPAA-aligned and GDPR-aligned agents. PII handling, retention policies, and audit logging are designed in from week one, not bolted on later.