SYS · ONLINEID-04.AX

[01]Intelligence layer

Intelligentsystemsfor real ops

We design, ship, and govern AI that sits inside products—models, pipelines, and interfaces teams can trust in production.

AI systems workspace
Latency42ms

    [02]Signal

    Built for teams that ship modelsnot decks

    Most “AI strategy” dies in slides. We wire intelligence into product surfaces, data layers, and ops rituals so impact is measurable every release cycle.

    0%Eval pass rate before prod gate
    0×Faster handoff to eng with system specs
    0wMedian to production pilot

    [03]Modules

    Four layers we assemble

    Pick a lane or stack the full vertical—from retrieval to runtime governance.

    01

    Knowledge & retrieval

    Chunking strategies, hybrid search, citation-safe RAG so answers stay grounded in your corpus.

      02

      Agents & orchestration

      Tool use, multi-step plans, and fail-soft loops that behave under load—not demos that break after hop three.

        03

        Evals & quality gates

        Offline + online evaluation harnesses, golden sets, and promotion criteria wiring to CI and release trains.

          04

          Platform & guardrails

          Routing, cost controls, red-team patterns, observability—everything between a prototype and an SLA.

            [04]Pipeline

            How intelligence moves from brief to runtime

            Phase 01

            Frame

            Map use cases, data rights, risk surface, and success metrics with product + legal in the room.

            Week 1–2
            Phase 02

            Prototype

            Thin slices, synthetic evals, early UX for trust signals—prove signal before platform spend.

            Week 3–5
            Phase 03

            Harden

            CI evals, tracing, fallbacks, cost budgets, and red-team passes wired to deployment gates.

            Week 6–9
            Phase 04

            Launch

            Canary traffic, runbooks, on-call paths, and handover kits engineering owns next.

            Week 10–12
            Phase 05

            Scale

            Model routing, multi-region, fine-tune options, and product experiments against live KPIs.

            Week 12+

            [05]Output package

            What lands in your repo

            Artifacts engineering can review, extend, and audit—not a zip of notebooks named final_v7.

            1. 01

              System map

              Architecture diagrams, data contracts, and threat notes for security reviews.

            2. 02

              Working branch

              Reference implementation with stubs for tools, model adapters, and config layers.

            3. 03

              Eval suite

              Datasets, scorers, and CI hooks so quality does not drift after handoff.

            4. 04

              Ops kit

              Dashboards, alert thresholds, incident runbooks, and cost budgets.

            5. 05

              Enablement

              Workshops for product, eng, and support so the system keeps improving in-house.

            [06]Engage

            Ready to put AI on a production schedule?

            Share your stack, constraints, and the job the model should do. We’ll return a framed approach within a few business days.