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Engineering company · Est. 2014

Production AI and enterprise software—
planned, built, and operated.

We ship battle-tested agents, retrieval layers, integrations and platforms your team can own: no black boxes, full observability, eval harnesses that catch failures before prod. Then we stay.

Trusted by 30+ teams shipping AI in production · Senior engineers only · Booking Q3 2026

Systems proven in production by
  • Dibstr
  • Bank Hapoalim
  • Web3M
  • Tarbut Sport
  • Coffix
  • Vegan Town
01
Why this company

Senior engineers. One team. Production first.

No slide decks or account managers. You get tight scope, code that survives code review by your team, and operations that continue long after we merge our last PR — whether the work is AI, platforms, or discovery.

  • 01

    You own the system

    Architecture your team can defend in review, code they can audit at 3am, runbooks that survive without us — no vendor black box.

  • 02

    Production is the bar

    Demos lie every time. The deliverable is software that runs reliably with monitoring, evals, and guardrails baked in from day one.

  • 03

    Work in the right order

    AI engineering first, enterprise platforms next, discovery or design only when the project demands it from real requirements.

02
What we ship

Three tiers of work—in that order.

AI engineering defines the company today. Enterprise platforms are the natural extension. Discovery and design enter only when concrete requirements pull them in.
01Primary

AI Engineering

We build agents and retrieval that survive production loads: eval harnesses that catch lies early, observability that scales, guardrails before the first prompt—not demo theater.

  • Agent and workflow systems (LangGraph, Temporal, custom orchestrators)
  • Retrieval pipelines with hybrid search and proper ranking
  • Model integrations across vendors—strictly neutral on weights and APIs
  • Evaluation frameworks, tracing, regression testing and guardrails
  • Deployment pipelines, monitoring, cost dashboards and fallbacks
Read the practice
02Secondary

Enterprise Systems

The boring but critical platforms, integration layers, data pipelines and replatforming that keep large systems running without drama.

  • Multi-tenant platforms and internal tooling at scale
  • Robust API and event-driven integration layers
  • Data infrastructure with proper observability and pipelines
Read the practice
Merges to main started week one. Weekly demos on real branches, evals that caught issues early, and handover docs our own engineers could actually use.
Senior Engineer · Platform Lead · Scaling SaaS
03
Evidence

What actually ships to production—not pilots.

M01Across production agents · 2023–2025
40+

Eval runs per model

M02Every AI engagement · 2024–2025
100%

Main branch merges from week 1

M03With runbooks and full observability · 2022–2025
12

Systems handed to client teams

Across 12 production engagements · 2022–2025
04
How we ship

Discovery, build, operate.

One consistent team owns it from initial scope through production support—so no knowledge gaps, no vendor handoffs, just continuous context.
01

Discovery

Two to six weeks mapping architecture decisions, scope, risks, and realistic estimates. You leave with documented plan and tradeoffs—even if we don't build it.

02

Build

Senior engineers only, weekly demos against real branches, merges into main from week one — no theatrical big reveal at the end.

03

Operate

Full monitoring, eval surfaces for AI, on-call rotations when agreed. We stay until the handover runbooks and ADRs are battle tested and owned.

Tell us what you need to ship.

We take limited new engagements per quarter. Send a concise brief — we reply with concrete scope, risks, and next actions from a real engineer.