Custom AI systems, agent workflows, data pipelines, and 24/7 operations for law, medical, and hardware teams. We build it, we deploy it, and we run it — so your team doesn't have to become an AI ops team.
Multi-year engagements with personal injury law, medical practice, and hardware teams.
Owned software outlives every SaaS vendor. We build it. We run it.
End-to-end delivery with one senior team — strategy, build, deploy, and the operations that keep it all running.
Owned multi-tenant systems built for your firm — with internal AI registries, governance, and per-team controls. Software you keep when we're done.
Example deliverables
Alternative you're weighingHiring a senior platform engineer in-house
The systems that actually do the work day-to-day — intake automation, document review, scheduling, follow-up — wired into your existing stack.
Example deliverables
Alternative you're weighingA generic automation shop stitching together Zapier and ChatGPT
Moving your data where the agents need it: typed schemas, retrieval indexes, and integrations with legacy systems most consultants won't touch.
Example deliverables
Alternative you're weighingA data engineering shop unfamiliar with AI workloads
We run what we build. On-call, monitoring, model updates, skill maintenance — a senior team behind your system around the clock.
Example deliverables
Alternative you're weighingSaaS vendor "support" that closes tickets without solving problems
Three industries where we've shipped — and where we run production systems today.
What we've shipped
We sit on the AI committee at a 100+ person personal injury firm. We replaced their case management system. We built and operate their AI intake. We run a custom AI registry that catches overlap across every internal AI tool.
Why this industry is hard
Attorney-client privilege, ethical walls, discovery obligations, and deadline-driven workflows that can't tolerate downtime.
Compliance posture
Privilege-aware data handling, US data residency, signed engagement agreements, code escrow available.
What we've shipped
Custom CRM and multi-portal platforms for therapy and cosmetic surgery groups. We integrate with legacy practice management systems (Goldmine and similar) that most consultants refuse to touch.
Why this industry is hard
HIPAA, multi-location coordination, legacy systems with no modern APIs, and scheduling that breaks if you blink.
Compliance posture
HIPAA-aware data flows, BAA available, US data residency, encrypted at rest and in transit.
What we've shipped
AI for kiosk and IoT products — embedded vs. cloud trade-offs, patent landscape research baked into discovery, edge-to-cloud model orchestration.
Why this industry is hard
Hardware constraints, intermittent connectivity, patent overlap risk, and supply chain coupling.
Compliance posture
IP-aware engineering, NDA-first discovery, prior-art audits as part of scoping.
24/7 operations isn't a support inbox. It's a senior team behind your platform: watching it, fixing it, and keeping it current.
Monthly retainer — per environment or per tenant.
In scope
The platform we built, the agents we deployed, the integrations we own, incident response, model updates, skill maintenance, monthly reporting.
Out of scope
Your help desk, your unrelated SaaS subscriptions, hardware support, IT generalist work.
Overage and incident-response terms are documented in the engagement letter.
| Environment | Status | Last incident | Uptime (this month) |
|---|---|---|---|
| PI Law — primary | Healthy | 12 days ago | 99.94% |
| Therapy group — east | Healthy | 31 days ago | 100% |
| Cosmetic surgery — multi-site | Watching | 2 hours ago | 99.71% |
| Hardware product co. | Healthy | 8 days ago | 99.98% |
Illustrative — real environments shown to clients only.
Model provider API regression
Summary. At 02:14, a primary model provider's completions endpoint began returning elevated 5xx errors. Affected: 6 agents across two client environments. Detected by our latency monitor within 3 minutes. Mitigated by failover to a secondary provider. Resolved at 03:09.
Timeline
Root cause
A provider-side deployment regressed request validation for a subset of tool-call payloads. On our side: the failover path existed but routed a narrower set of skills than it should have.
What we changed
Client impact. Zero workflow disruption. 41 inbound tasks were rerouted through the secondary provider during the incident and completed within normal SLAs.
Representative example — illustrative, not a specific client incident.
Four stages from renting software you don't control to running a platform you own.
We map what your firm currently rents that you should own.
DeliverableA 1-page SaaS replacement map, ranked by leverage and risk.
One end-to-end thing live in production. Not a demo. Not a proof of concept.
DeliverableA working system your team uses every day.
We absorb adjacent SaaS into the platform you own. Registry, governance, and multi-tenant patterns emerge here.
DeliverableAn owned platform replacing 3–5 vendor systems, with internal AI registry and per-team controls.
We run what we built.
DeliverableMonthly ops report, on-call coverage, an evolving roadmap, and quarterly platform review.
Real client quotes are being collected and approved. Slots below are placeholders.
// pending: anonymized quote — Managing Partner, 100+ person personal injury firm
// pending: anonymized quote — Operations lead, multi-location therapy practice
// pending: anonymized quote — Founder, hardware product company
What we use
What we don't use
What you actually get, head to head.
| SilverArrows | In-house hire | Traditional dev shop | Generic AI shop | Big consultancy | |
|---|---|---|---|---|---|
| Time to first production system | 4–6 weeks | 3–6 months | 2–4 months | 1–2 weeks | 3–9 months |
| Code ownership | You | You | You | Often them | You (eventually) |
| Senior engineer on every project | Yes | N/A | Sometimes | No | No |
| 24/7 operations included | Yes | Hire separately | No | Locked-in vendor | Yes (expensive) |
| Can absorb existing SaaS | Core competency | Depends | Maybe | No | Yes |
| Minimum engagement | $$ | $$$$ (salary+benefits) | $$ | $ | $$$$$ |
A small senior team. The principal is on every engagement. We grow by depth, not by headcount.
Code escrow, runbooks, and documented handoff terms. Your platform survives us — that's the point of owning it.
No. The cross-pollination across clients is part of the value. If you want full-time AI engineering inside your firm, we can help you hire it.
We start with a paid pilot — one system live in production, typically 4–6 weeks — then a monthly retainer per environment. We don't take engagements smaller than that; below it, you're better served by tools you can buy off the shelf.
Yes. Both. Standard practice.
You do. From day one.
Those are fine for prototypes. They break under production load, can't be observed properly, and become their own vendor lock-in. We build owned systems that don't.
Severity-1 incidents get a response within 30 minutes, 24/7/365. The full operations model is on the live-ops window.
BAA available. HIPAA-aware data flows. We've shipped under it.
Most firms are renting AI tooling from vendors who will raise prices, change terms, or get acquired. Our worldview: AI tooling is too core to outsource. We help you own it.
I started Two Two because I kept watching good firms get trapped by their own software.
Every firm had the same problem: a stack of SaaS tools nobody fully controlled. Per-seat pricing that crept up every renewal. Vendors that changed terms, got acquired, or quietly deprecated the feature a whole workflow depended on. AI made it worse — suddenly there were ten AI tools across five departments, no inventory, no governance, and no one who could say what they all did.
The standard answer is to bring in an outside shop. Most of them fail at this, and they fail the same way: they ship a demo, hand you a Zapier flow, and leave. The thing they built isn't observable, isn't owned, and isn't run by anyone after the invoice clears. Six months later it's another vendor you can't fire.
I think AI tooling is too core to a firm's operations to rent. If an agent is doing your intake, reviewing your documents, or scheduling your patients, that's not a feature — that's infrastructure. Infrastructure should be owned.
So that's what we build: AI platforms a firm actually owns, with the registry and governance to keep them sane, and the 24/7 operations to keep them running. We sit on AI committees. We replace case management vendors. We run agent fleets at 2am so our clients' teams don't have to.
The hardest lesson from running production AI is that the model is the easy part. What's hard is the operations — the failover when a provider regresses, the eval when an upstream API shifts, the runbook for the incident at 3am. Most shops skip that work because it doesn't demo well. It's also the only part that matters once the thing is live.
We're a small senior team. I'm on every engagement. We grow by depth, not headcount.
Book a call or tell us about your stack below. We reply within one business day.
Async — tell us about your stack
$ deploy silverarrows --env=prod✓ inference pipeline ready✓ secure data vault mounted✓ compliance checks passed✓ latency 220ms p95 — shipping it
This is the boring part. We make it look easy.
Full 60–90s product walkthrough — coming soon.
Replaced, consolidated, or never delivered.
The firm ran on a major case management SaaS, RingCentral, and a sprawl of AI tools that had accumulated across departments. No central inventory. No governance. Per-seat costs rising. Vendor lock-in across the stack.
We joined the firm's AI committee with leadership. We built an internal AI Registry inside the firm's own platform — a catalog of every AI system running, with overlap detection across capabilities. As the registry surfaced redundancy, we absorbed the case management vendor's functionality into the owned platform: intake flows, document handling, scheduling, and follow-up. We rebuilt the intake system end-to-end on owned infrastructure with AI-assisted triage.
An owned multi-tenant platform on Postgres and vector indexes, agent orchestration built on MCP, deployed on managed cloud infrastructure. Full detail on the stack window.
[Pending — client-approved anonymized quote about the outcome]
— Managing Partner, 100+ person personal injury firm
Field notes, monthly. One essay, one short note, one link. No promo.
Essay in draft — Omri is writing this one.