MISSION BRIEF
We embed AI where it actually matters — not as a gimmick, but as a core feature. From conversational interfaces to intelligent automation, we build AI systems that understand context and deliver real value.
CAPABILITIES
MISSION INTEL
CLASSIFICATION
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MISSION XP
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▸ OVERVIEW
Most "AI features" are demos in disguise — a chat box bolted onto a SaaS to satisfy a board slide. We build the other kind: AI that sits on the critical path of your product, doing measurable work users actually pay for. Retrieval pipelines that ground answers in your data, agents that complete multi-step workflows, structured-output systems that replace brittle rule engines.
Every system we ship runs against real evaluations before it sees a user. We instrument tokens, latency, hallucination rate, and cost per request from day one, so you can scale with conviction instead of crossing your fingers. The result is custom software where AI is a feature you can defend in a roadmap review — not one you have to apologise for at the next QBR.
▸ WHAT WE DELIVER
Hybrid retrieval (vector + keyword + rerank) tuned for your corpus, with citations, freshness controls, and eval harnesses you can run on every release.
Tool-using agents with structured outputs, guardrails, and deterministic fallbacks — not autonomous black boxes that hallucinate at 2 a.m.
Drafting, summarisation, classification, extraction — embedded where users already work, with caching and streaming for sub-second feel.
Golden-set tests, regression alerts on model swaps, side-by-side comparisons across Claude, GPT, and Gemini.
Per-feature token budgets, alerting on cost spikes, and tracing so you can debug a bad answer down to the retrieved chunk.
Prompt-injection mitigation, PII redaction, rate limits, and content policy enforcement appropriate to your industry.
▸ WHO IT'S FOR
▸ OUTCOMES YOU CAN EXPECT
▸ HOW WE WORK
We co-write the eval set first. If we can't measure success, we don't start coding.
Working slice in 2–3 weeks, scored against the eval set across multiple models.
Caching, observability, guardrails, infra, CI/CD with regression tests on prompts and outputs.
Ship behind a flag, watch the dashboards, tune retrieval and prompts on real traffic.
▸ FREQUENTLY ASKED
Anthropic Claude, OpenAI, Google Gemini, and open-source models on AWS Bedrock or self-hosted via vLLM. We design model-agnostic so you can switch when pricing or capability shifts.
A scoped prototype lands in 2–3 weeks. Production-ready, monitored, and on your CI/CD pipeline is typically 6–10 weeks depending on data complexity and compliance scope.
Yes. We integrate into existing Next.js, NestJS, Django, Rails, .NET, and Java backends. We don't require a green-field rewrite to add AI.
Semantic caching, prompt compression, model routing (cheap model for easy queries, premium model for hard ones), per-user rate limits, and cost dashboards with alerts.
We default to providers with zero-retention enterprise agreements, support self-hosted models for sensitive workloads, and implement PII redaction in the retrieval layer.
▸ THE ITI-X DIFFERENCE
We architect AI into your system from the ground up — with proper fallbacks, rate handling, and retry logic.
READY TO DEPLOY
Let's build, secure, design, or lead — together.