Currently accepting new engagements · limited slots

Production AI in 30 days,inside your infrastructure.

Most enterprise AI takes 6 to 9 months and never reaches production. We compress that into a month. Senior engineering pods, embedded in your stack. Paid monthly. Gone the moment we stop earning it.

Book a 20-min call How we ship in 30 days

30 days

Whiteboard to production, every engagement

6–9 mo

What most teams spend stuck in pilot

Week 1

Working prototype on your calendar

Your repo

Every line of code, from day one

We ship across these sectors. Client names withheld per contract.

12 categories · 4 continents

Healthcare operations

B2B fintech

Freight & logistics

Legal services

Insurance

HR & payroll tech

Hospitality

E-commerce & DTC

Property management

Industrial supply

Field services

K-12 ed-tech

Healthcare operations

B2B fintech

Freight & logistics

Legal services

Insurance

HR & payroll tech

Hospitality

E-commerce & DTC

Property management

Industrial supply

Field services

K-12 ed-tech

Why we exist

The gap between “we should build this” and “this is in production” has gotten worse, not better.

The models keep improving. The path to production hasn’t. Teams spend two quarters on a pilot, watch it stall in security review, and the budget evaporates with nothing in front of users. That’s the gap we built milebits to close.

73%

of enterprise AI pilots never reach production.

MIT Sloan / BCG, 2024

6–9 mo

average enterprise AI build time, kickoff to live traffic.

Industry surveys, 2024–25

$1.7M

median cost of an AI pilot that quietly dies in the demo folder.

Gartner, 2025

9 weeks

average vacancy for senior AI engineering hires in 2026.

Levels.fyi / LinkedIn hiring data

Our answer

A small team of senior engineers, embedded in your infrastructure, shipping to production in 30 days. Not slides. Not pilots. Not a proprietary platform you’ll have to migrate off of in a year. Working software, in your repo, by week four.

What we ship

Six things we're good at. We'll tell you if your problem isn't one of them.

Each item below is something our pods deliver inside a Sprint or Pod engagement. Pricing lives in one place, further down. You pick the tier, we configure the work.

01Sprint or Pod

AI agents that actually ship

Not a demo. Not a pilot. A working agent in your stack, handling real load by week four.

Frontier model of your choice routed through your data. Snowflake, Postgres, Notion, whatever you have.
Failure modes we obsess over: hallucinations, drift, runaway costs, prompt injection.
Eval harness from day one. Accuracy is a number you set, not a vibe we report.
Observability stack in your account. Every prompt, completion, and cost line queryable.

What we measure

Tickets deflectedTime-to-resolution droppedCost-per-interaction tracked

02Sprint or Pod

Voice AI for the phones nobody picks up

Inbound, outbound, after-hours, overflow. Sounds human, books the meeting, doesn't quit at 5pm.

Built on Retell, Vapi, or your provider of choice. We don't sell you a stack.
HIPAA-aware setups for healthcare front offices, BAA-ready.
Routes to a human the second confidence drops below your threshold.
Per-minute economics you can actually live with, not the marketing number.

What we measure

After-hours capture rateMeetings booked per dollarHuman-handoff rate

03Pod

Copilots trained on what your team knows

RAG done by people who've watched RAG go sideways. Real retrieval, real evals, real answers.

Your docs, tickets, wiki, Slack history. Chunked and indexed properly, not naively.
Permissions respected. If a user can't see the source, the copilot won't quote it.
Eval harness from day one. Accuracy measured before adoption is celebrated.
Plugs into Slack, Teams, your app, or a standalone surface you control.

What we measure

Tier-2 deflectionTime-to-answerCitation accuracy

04Pod or Fleet

Embedded engineering pods

Two senior engineers and a fractional CTO in your Slack. Daily standups. Code in your repo from day one.

Decade-plus average experience. No offshoring. No juniors. No PMs in your way.
We work to your sprint cadence, your CI, your branching model. Not ours.
Hiring plan, infra plan, due-diligence prep, all included if you need it.
Pause or end on 30 days' notice. We're here as long as we're earning our keep.

What we measure

Roadmap velocityTime-to-hire bridgedAudit-readiness reached

05Sprint or Pod

SOC 2 without the theater

We don't sell you Vanta. We sell you a SOC 2 Type II audit you'll actually pass.

Vanta or Drata partner pricing passed straight to you (20–40% off list).
Policies written for your stack, not a template from 2019.
Auditor introductions, scoping calls, and evidence collection handled.
Most clients are audit-ready in 6 to 10 weeks, not six months.

What we measure

Pipeline unblockedTime-to-auditExceptions on first pass

06Sprint or Pod

Internal tools & automation

The stuff your ops team is doing in 14 spreadsheets and a Slack channel right now.

Retool, n8n, Make, or hand-rolled Next.js. Whatever fits the actual job.
Self-hosted by default. You own it. We don't bill per workflow or per seat.
Integrations with HubSpot, Stripe, Salesforce, NetSuite, and the long tail.
Built once, maintained on a small retainer if you want it maintained.

What we measure

Hours reclaimed/weekError rate droppedPer-task SaaS fees eliminated

The real comparison

Most teams aren’t deciding between us and another agency. They’re deciding whether to hire two engineers.

Hiring is usually the right answer eventually. It’s rarely the right answer now. Here’s the honest math on the next twelve months.

Axis

Hire 2 senior engineers

Engage a milebits Pod

Time to first commit in your repo

8–14 weeks (post-offer, post-notice, post-onboarding)

Day 1

Time to first production deploy

4–6 months (ramp, context, first non-trivial PR)

Week 3

Year-one all-in cost for 2 senior engineers

≈ $480K (salary + equity + benefits + tooling + recruiter fees)

≈ $245K for a full Pod, 10 months

Risk of a mishire

Industry rate ~1 in 4, plus a 6-month decision cycle to undo

Pause or end on 30 days’ notice, no severance

AI-specific production experience

Scarce. Top candidates have 6–9 week vacancy averages.

Every engineer staffed has shipped production AI before

When the work is done

Awkward. You let people go or invent a new charter.

We leave the runbook and the code. You keep going.

When hiring is the right call: if you’ve already shipped a v1 to production and you need someone to own the system for the next three years. We’ll tell you that on the first call. Several clients have gone from us → their own AI team in 6–12 months, with us handing over the keys.

How we work

Working software in week one. Production by week four. Or we don't bill you for week five.

We ship on a cadence that's uncommon for the category. We can do it because every engineer staffed has shipped this stack before, and because the scope of week one is written down before we touch a keyboard.

Week 01/5

The 20-minute call

You tell us what's broken. We tell you whether we should be the ones fixing it. If we're not, we'll usually know somebody who is.

You get

Honest yes or no, in writing, before you leave the call.

Week 12/5

Working prototype

Two senior engineers in your Slack on day one. By Friday there's a thing you can click, prod-quality enough to show your team.

You get

Loom walkthrough, sandbox URL, weekly demo on the calendar.

Week 23/5

In your repo

Code lands in your GitHub. PRs reviewed by your team. Infra in your cloud account, your IAM, your observability stack. Never ours.

You get

PRs merged, env vars handed off, runbook drafted.

Week 34/5

Behind a flag

Deployed to production. Gated by your feature flag tool of choice. We dogfood for 48 hours, then your team picks the rollout pace.

You get

Staged rollout plan, observability dashboards, on-call rotation.

Week 4+5/5

Shipping for real

Full traffic. Iteration begins. Weekly demos continue. You can pause us at 30 days' notice from this point on. No annual lock-in, ever.

You get

Real users, real cost line items, real numbers in your dashboard.

How we keep this honest

Promises are cheap. Mechanisms aren’t.

Every claim on this page is enforced by something operational. If we can’t name the mechanism, we don’t make the claim. Here are the six questions every serious CTO asks us before signing.

01Mechanism

How do I know you’re actually shipping, not building toward a demo?

PRs land in your repo daily. Demos happen every Friday.

▸Every PR opens with a description, tests, and a 60-second Loom. No “trust us” merges.
▸A standing 30-minute demo on your calendar every Friday, your team picks who attends
▸We work on your branch protection rules. If you require two reviewers, we require two reviewers.
▸Revoke our repo access on a Monday morning and the system you have keeps running

02Mechanism

How do you prevent the AI from doing something embarrassing?

An eval set you sign off on, before anything reaches your users.

▸We build the eval set with your subject-matter experts in week one. Your prompts, your expected outputs.
▸Accuracy threshold is a number we agree on before launch. We don’t flip the flag until we hit it.
▸Every AI call routes through a confidence threshold. Under it, we hand off to a human, log the case, and feed it back into evals.
▸Hallucinations are tracked in your dashboard as a metric, not discovered in a post-mortem

03Mechanism

How do you keep the model bill from blowing up at 2am?

Per-tenant token budgets and a cost alarm wired to your Slack.

▸Every integration ships with a per-tenant token budget. Runaway loops hit the budget, not your card.
▸Cost alerts land in your Slack at 80% of the budget, well before anyone notices
▸Model selection is layered. Cheap model for cheap tasks, premium model only when accuracy demands it.
▸Caching, batching, and prompt compression applied by default, not as an optimization later

04Mechanism

What happens if we want you gone in 90 days?

You get a runbook, a recorded handover, and an empty calendar invite for us.

▸At engagement end: a written runbook for every system we built, kept in your wiki
▸A 60-minute recorded walkthrough of each system with your in-house engineer
▸A two-week overlap with whoever’s taking over (your hire, your existing team, another vendor)
▸Our repo access, infra access, and Slack invites revoke on day one of the wind-down

05Mechanism

How do you stop us inheriting a black box?

Every prompt, completion, latency, and cost line is queryable from day one.

▸Helicone or Langfuse wired up in week one. Every model call logged, searchable, exportable.
▸Standard observability stack (OpenTelemetry / Datadog / your APM) for the non-AI surface
▸Architecture diagrams in your repo, kept current. Not in a Figma file we own.
▸On-call rotation included from day one. Your team is in it, not just ours.

06Mechanism

What if your engineer leaves mid-engagement?

The pod outlasts the individual. Everything is documented and pair-loaded.

▸Pair coverage on every workstream. Two engineers know each system, not one.
▸We staff replacements within five business days, no scope slip
▸Onboarding doc for new pod members lives in your repo, written by us, vetted by your team
▸If you don’t like the replacement, we swap again. No conversation, just done.

The deal

Six things we won’t do, and six we always will.

We’d rather lead with what we don’t do. It’s shorter, and it tells you whether we’re actually the same kind of team you’ve been burned by before.

What we don’t do

✕Pilots that quietly die in the demo folder six months later
✕Junior engineers learning your stack on your dime
✕Twelve-month contracts with three-month opt-outs buried on page 14
✕Vendor lock-in disguised as a ‘proprietary platform’
✕Subcontracted offshore work pretending to be senior engineering
✕PMs whose only job is forwarding Slack messages back to us

What we always do

✓Code in your repo, infra in your cloud, on day one. Every line, every commit.
✓Working prototype in week one, written scope before that
✓Senior engineers only, decade-plus production experience
✓Monthly billing, pause on 30 days’ notice, no annual lock-in, ever
✓Partner pricing on Vanta, Drata, Retell, Vercel passed straight through
✓Weekly demo on your calendar, daily PRs, on-call rotation we share

Recent work

Three recent engagements. Wins, and the parts that almost broke.

Client names withheld per contract. The constraint moments below are what actually matters. The wins are the easy part of the story.

CASE / 017 weeks

Multi-clinic healthcare group

Healthcare ops · 14 clinics · ~220 staff

“Two other vendors pitched us 6-month pilots. milebits had something running for two clinics in 19 days. We rolled the rest a month later.”
VP Operations · healthcare client

The problem

Front desks were drowning in inbound calls. Patient pre-authorization was running 4–6 business days, with material billing delays piling up downstream.

What we shipped

HIPAA-aware voice agent handling intake calls + a copilot for pre-auth document review. BAA in place by week three.

What didn’t work first

Week-two prototype failed on roughly 14% of calls. Patient population had accent diversity the default speech model couldn’t handle. We re-trained on 200 sample calls before expanding past the pilot clinics. Cost us a week, saved us a rollout.

94%

of intake calls answered on first ring

1.4 days

average pre-auth turnaround (was 4–6)

5 weeks

to roll from a 2-clinic pilot to all 14

CASE / 029 weeks

B2B fintech, Series A

Financial services · ~40 employees

“We’d budgeted four months. We shipped in nine weeks. The auditor said it was the cleanest evidence package she’d seen all year.”
Co-founder & CTO · fintech client

The problem

Six enterprise deals stuck waiting on SOC 2 Type II. Procurement at every lead refused to move without it. No internal security headcount.

What we shipped

Vanta setup with partner pricing, policy library written for their actual stack, auditor introductions and scoping calls handled, evidence collection automated.

The thing nobody scoped

SOC 2 didn’t unblock the deals on its own. Every enterprise procurement team also asked for an AI-acceptable-use policy, which didn’t exist yet. We wrote one from scratch with their general counsel. Two weeks we hadn’t scoped, but the deals didn’t close without it.

Pipeline

unblocked within 60 days of audit close

9 weeks

from kickoff to passing Type II

exceptions on first audit pass

CASE / 035 weeks

Mid-market freight brokerage

Logistics · 60 dispatchers

“Other firms wanted us on their platform forever. milebits built it on our infra and walked us through the code. We own every line.”
Head of Operations · logistics client

The problem

Dispatchers were spending 3+ hours a day in 14 different spreadsheets reconciling carrier rates, load assignments, and exception reports. Errors were a real, recurring cost line.

What we shipped

Self-hosted n8n workflows + a Retool dispatcher console connected to their TMS, accounting system, and three carrier APIs. All on their own AWS, fully owned.

The trade we made

Their TMS exposed a SOAP API last updated in 2009. The clean play was lobbying for an API rewrite. The shippable play was writing a shim layer in two days and moving on. We shipped the shim. It’s still in production a year later, untouched.

22 hrs

reclaimed per dispatcher per week

73%

drop in reconciliation errors month over month

in per-task SaaS fees. Owned, not rented.

The stack

We're opinionated, but we'll meet your stack where it is.

We don't sell you a proprietary platform. The categories below are what we use most. We track new frontier model releases and evaluate them for production fit within two weeks. The list is current, not exclusive.

Models

Claude (Anthropic)
GPT (OpenAI)
Gemini (Google)
Llama (Meta)
Voyage embeddings
Cohere rerank

Orchestration

LangGraph
Mastra
Inngest
Temporal
Trigger.dev
n8n (self-hosted)

Voice

Retell
Vapi
Bland
Deepgram
ElevenLabs
Twilio

Data

Postgres + pgvector
Snowflake
Pinecone
Turbopuffer
Clickhouse
dbt

App layer

Next.js
Remix
Hono
tRPC
Drizzle
Prisma

Infra

Vercel
AWS
Cloudflare
Fly.io
Render
Modal

Observability

Helicone
Langfuse
Datadog
Sentry
OpenTelemetry
Grafana

Compliance

Vanta (partner)
Drata (partner)
SOC 2
HIPAA
GDPR
ISO 27001

On something else? Bun, Hono, ScyllaDB, Convex, Pulumi, OpenSearch, Workers AI, your own internal platform. Say so. We've probably shipped on it.

Pricing

One pricing model. Three tiers. No surprises after the contract.

Pick the tier that fits the scope. Inside any tier, we configure the work from the services menu above. Everything is monthly. No annual contracts, no setup fees, no per-seat, no per-workflow. Pause if you need to. Fire us if we're not earning our keep.

Sprint

tier

$9,800/ month

One senior engineer, one well-scoped problem, one Slack channel.

Best for: a single agent, a focused integration, an internal tool that needs to exist by next month.

✓1 senior engineer, ~30 hrs/week
✓Weekly demo, daily Slack
✓Code in your repo, infra in your cloud
✓Weekly written status, no decks
✓Pause or end on 30 days' notice

Start a sprint conversation →

Starts in 7 days. We don't begin until we've named the outcome together.

Most chosen

Pod

tier

$24,500/ month

Two senior engineers + a fractional CTO. Enough horsepower to ship a full system, not a feature.

Best for: an end-to-end build (agents + voice + tooling), or a Series A rebuild, or a 0→1 launch.

✓2 senior engineers + fractional CTO
✓Weekly demo, daily standup in your Slack
✓Hiring plan, infra plan, on-call rotation included
✓Partner pricing passed through (Vanta, Retell, Vercel)
✓Pause or end on 30 days' notice
✓Quarterly business review with leadership

Start a pod conversation →

Most clients land here. Starts in 14 days.

Fleet

tier

Let's talk

Multiple pods, embedded leadership, and a roadmap we own with you. Built for scaleups and PE portcos.

Best for: 3+ concurrent workstreams, a CTO transition, or a portfolio playbook across multiple companies.

✓Multi-pod engagement, shared leadership
✓Embedded VP-level technical leadership
✓Quarterly board-ready architecture reviews
✓Custom SLA, custom MSA, custom everything
✓Dedicated security + compliance liaison

Start a fleet conversation →

We take two of these per quarter. Conversations start with a 45-min call.

Risk reversal: if week one doesn't produce a working prototype you can show your team, we don't bill for week two. The mechanism: every engagement starts with a written scope of what “working prototype” means before we touch a keyboard. Disagree on the artifact at the demo, you don't pay.

Questions

The questions every client asks us in the first 20 minutes.

Full-time engineers are usually the right answer eventually. We're the bridge. You hire us when you need someone shipping by Monday and a job posting won't close for months. When you've hired the right team, we hand off everything. The code is already yours, the infra is already in your cloud, the runbook is already written. Working ourselves out of the job is the goal, and we don't mind when it happens.

Most codebases are. We're not here to judge. We've worked in Rails monoliths older than some of our engineers, in 4-year-old Next.js apps with three router migrations, and in greenfields. We adapt to your conventions, your CI, your branching model. We won't try to rewrite your stack to use our preferred one. That's a tell of an agency that's actually selling templates.

Real answer: our MSA is signed once, and engagements run on monthly purchase orders. You can pause or end at any time on 30 days' notice. Most clients stay for many months on rolling terms, because we keep earning it. Not because they signed something they can't get out of.

Every engineer staffed on your project has shipped production AI, voice, or compliance work before. Most have a decade-plus building software. We don't post bios on the site because we don't think you should hire us off LinkedIn. We'd rather introduce you to whoever's staffed on your project on day zero, on a call, and let them earn the trust themselves.

Sprint engagements: typically 7 days from signature. Pod engagements: 14 days. Sometimes faster when a pod is between projects. We won't lie about availability. We say 'we can't take you for six weeks' more often than 'we can start Monday.'

Mostly because we don't try to be everything. Six services. Senior engineers only. Code in your repo. Monthly contracts. Weekly demos. Founder-led. No PMs in the loop, no offshore handoff, no proprietary platform. If you've been burned, you know what bit you. We've tried to make ourselves the opposite of that.

Day 1: kickoff call, Slack channel created, repo access exchanged, problem statement written and pinned. Day 2: scoping doc with the smallest shippable thing identified. Day 3–4: working prototype in a sandbox. Day 5: Loom walkthrough, demo on your calendar for next Friday. Week one is choreographed. The improvising starts in week two.

Yes to all three. We're set up to handle vendor security questionnaires quickly. Most come back within a week. BAAs are standard for healthcare engagements and we'll have one ready for legal review on day one. We aim to be the easiest vendor your procurement team has dealt with this quarter.

Limited engagement slots open

The hard part isn't building the AI.It's shipping it.

Twenty minutes on a call. Bring the messiest problem you have. We'll tell you, on the call, whether we're the right team for it.

20 min

Honest first call

7 days

Sprint engagement starts

Week 1

Working prototype

30 days

Cancel any time, in writing

Prefer email? hello@milebits.tech