Neume Labs
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Engineers on monthly retainer

We embed engineers inside your company until it runs on AI.

Forward deployed engineers for companies with 50 to 5,000 people. One engineer sits with your teams, ships the first system into production in six weeks, and stays on a monthly retainer until AI is how the work gets done.

Book a call with an engineerHow it works

47+ production systems · 6 weeks to production · 3.2x productivity at 90 days

01The model

Not a consultant. Not a dev shop. An engineer on your floor.

A forward deployed engineer is a senior engineer who works inside your company rather than for it. They sit with the claims processor, the dispatcher, the underwriter. They find the workflow where AI pays off first, build the system on top of the software you already run, ship it to production, and train your people to run and extend it. Then they move to the next workflow.

In 2019 the hard part of enterprise AI was the model. Today the models are commodity infrastructure. The hard part is the twenty-year-old ERP, the undocumented process, the compliance rule nobody wrote down, and the operations manager who has watched three digital transformations fail. That is an engineering problem, and it is solved on site.

Consultancies

Deliver a strategy deck and leave. Cannot write production code.

Writes the code. Stays until it runs.

Dev shops

Build what you spec. Never see your operations.

Sits in your operations. Finds what to build.

Hiring

Six months to hire one AI engineer who starts from zero.

Arrives in a week with patterns from 47 deployments.

SaaS tools

Horizontal products configured for nobody in particular.

Systems built for your data, your edge cases, your compliance.

We don’t consult. We engineer intelligence.

02How it works

Contact. Audit. First deliveries. Monthly.

From the first call to a system in production in six weeks. Then a retainer that scales up or down every month.

01 / Contact30 minutes

A call with an engineer, not a salesperson.

We find out whether there is a fit and which workflow to start with. No deck, no discovery workshop, no proposal cycle.

Call with an engineer30 min
Who
Your COO, your head of operations, and a Neume engineer.
We ask
Where the work piles up. Which systems it lives in. Who reviews it today.
You get
A straight answer on fit, and the workflow we would start with.
Nothing to prepare. Bring the person who owns the process.

02 / AuditWeek 1

The engineer embeds with the teams doing the work.

Every workflow mapped and ranked by AI leverage. The output is a 90-day build plan with the first systems specified and ROI attached to each.

Workflows ranked by AI leverageWeek 1 · every department
  • 01

    Document intake and data entry

    Keyed by hand from PDFs and email

    Build first
  • 02

    Invoice and billing audit

    Checked line by line against contract

    Queued
  • 03

    Customer onboarding

    Days of back-and-forth per account

    Queued
  • 04

    Month-end reporting

    Rebuilt in spreadsheets every cycle

    Queued
90-day build plan signed. First system specified, ROI attached.

03 / First deliveriesWeeks 2 to 6

The first system ships to production with human review switched on.

Real data, real compliance constraints, real users. This is the proof, before any retainer.

First system Production

Human review

  • WK 02All
  • WK 04All
  • WK 06Flagged

Starts at 100% review. Falls as the system earns trust.

6 wks

kickoff to production

47+

systems in production

Runs on your data, in your repository, on your infrastructure.

04 / MonthlyMonth 2 onward

The engineer stays. Department by department, workflow by workflow.

Review thresholds fall as the systems earn trust. Scale the engagement up or down each month. Our revenue depends on it working, so we stay until it does.

Retainer roadmapOne engineer · embedded
  • M2Second workflow, same departmentshipped
  • M3Next department onboardedshipped
  • M4Review threshold loweredin review
  • M5Third department scopedscoped

3.2x

productivity, day 90

8x

at twelve months

0

data incidents

Embedded. Not engaged.

03Field reports

What production looks like when the engineer is in the building.

Three engagements, written the way an engineer would report them. Names withheld under NDA. Every figure confirmed.

Report 01Logistics$120M third-party logistics6 weeks to production

Before

Every new carrier contract meant hiring clusters of bill-of-lading clerks. Twelve people on manual data entry, a 6% error rate, and about $340K a year in rework. The board had denied headcount three quarters running.

Built

$30M in new revenue absorbed. Zero back-office hires.

An autonomous document agent that reads bills of lading across seventeen carrier formats, checks line-haul and accessorial charges against the master contract repository, and processes invoices end to end. Humans review the 6% it flags.

94%

Invoices straight-through

0.3%

Error rate, from 6%

9

Clerks redeployed

Report 02Financial services$85M wealth management8 weeks to production

Before

Compliance officers reading 200-page trust documents by hand to find ultimate beneficial owners. Two high-value prospects had already left for firms that onboarded faster.

Built

Client onboarding from 14 days to 4 hours.

A compliance copilot trained on the firm's own regulatory framework. It draws ownership hierarchies from unstructured legal documents, flags politically exposed persons, screens against sanctions lists, and hands analysts a risk assessment with page-level citations.

78%

Less KYC processing time

2 days

Audit prep, from 3 weeks

$1.2M

Compliance hiring avoided

Report 03InsuranceMid-market MGA7 weeks to production

Before

Senior underwriters spending 60% of their day keying broker submissions from 100-page loss runs and ACORD forms. Quotes took five days. The best brokers had stopped sending business.

Built

Premium capacity up 300%. No new underwriters.

An ingestion layer that intercepts broker emails, reads loss runs with insurance-trained document intelligence, maps ACORD fields, runs the rules engine, and pre-populates the underwriting workbench with verified data.

300%

Premium writing capacity

Same day

Quote turnaround, from 5 days

0

New underwriting hires

47+

Production systems deployed

6 wks

Average kickoff to production

3.2x

Productivity gain at 90 days

8x

At twelve months

0

Data incidents

04AI native, defined

Five levels. The engineer moves you up one workflow at a time.

AI native means AI is inside the workflow, not beside it. Every recurring process has been examined for what an agent does and what a human must do. Every knowledge worker has a copilot wired to the company’s own data. And the people who work there can extend the systems after the engineer leaves. The audit tells you where you are today.

Audit · Week 1

Where does the company sit today?

Five levels · one ladder
  1. 0level

    Curious

    ChatGPT on personal accounts. No policy, no systems, no data connected.

  2. 1level

    Experimenting

    A pilot or two in a sandbox with clean data. Nothing in production.

  3. 2level

    Operational

    One or two systems live in one department, with humans reviewing every output.

  4. 3level

    Embedded

    AI inside the core workflows of most departments. Humans handle the exceptions.

  5. 4level

    Native

    New work is designed AI-first by default. Your own team extends the systems.

Most companies arrive at level 0 or 1. The first system takes them to level 2 in six weeks.

05What we build

Fourteen systems an engineer ships. All built in your repository.

The audit decides which one comes first. Each brief covers what the system is, how it is built, and what the first weeks look like.

01

Autonomous Agents

Most enterprise AI stops at suggestions. Autonomous agents perceive context, reason through ambiguity, and take action across your systems -- completing in seconds what previously required hours of human coordination across teams and tools.

Read the brief

02

Team Copilots

Not another chatbot. Team Copilots are role-specific AI systems that live inside your workflows — drafting, researching, analysing, and recommending in real time. They learn your processes, respect your compliance boundaries, and get sharper with every interaction. Production-grade in 4–6 weeks.

Read the brief

03

Document Intelligence

Combine state-of-the-art OCR with large language models to extract, classify, and validate data from invoices, contracts, claims, compliance filings, and any unstructured document -- at enterprise scale with human-grade accuracy.

Read the brief

04

Decision Engines

Replace gut-feel decisions and static spreadsheets with intelligent systems that ingest thousands of data points, weigh competing factors in real time, and deliver explainable recommendations -- so your best people spend their time on judgment, not data wrangling.

Read the brief

05

Workflow Automation

Replace brittle rule chains and manual handoffs with AI-orchestrated workflows that route, decide, and escalate based on context -- not just pre-programmed if/then trees.

Read the brief

06

Predictive Analytics

Turn operational data into demand forecasts, risk scores, and opportunity signals that compound in accuracy over time. No data-science team required -- Neume deploys production-grade predictive models with human-in-the-loop validation, so your team acts on insights, not equations.

Read the brief

07

Conversational AI

Deploy AI agents that understand context, handle complexity, and operate across chat, voice, and messaging channels — built around your business logic, not a generic template.

Read the brief

08

Data Integration & ETL

Enterprises lose 30-40% of analyst capacity to manual data wrangling -- reconciling mismatched schemas, chasing down custodian feed failures, and hand-mapping fields between systems that were never designed to talk to each other. Neume replaces brittle, rule-based ETL with AI agents that understand your data semantically, adapt to schema drift automatically, and deliver clean, reconciled datasets to downstream systems in hours instead of weeks.

Read the brief

09

Knowledge Management

Stop losing critical expertise when employees leave. Neume indexes every document, email, ticket, and system of record into a unified knowledge layer -- so your entire organization can find answers in seconds, not hours.

Read the brief

10

Compliance & Audit AI

Regulated enterprises spend 15,000-40,000 person-hours per year on manual compliance activities -- evidence gathering, control testing, policy mapping, and audit preparation -- that are fundamentally pattern-matching and document-processing tasks. Neume's Compliance & Audit AI compresses these cycles from quarterly marathons into always-on, machine-verified assurance with human oversight at every decision boundary.

Read the brief

11

Computer Vision

Turn cameras, scanners, and satellite feeds into structured, actionable data -- replacing manual visual inspection with auditable, sub-second analysis at any scale.

Read the brief

12

Process Mining

Neume's AI process mining reconstructs real execution paths from system event logs, surfaces bottlenecks invisible to management, and quantifies the gap between documented procedures and ground-truth behavior -- in weeks, not quarters.

Read the brief

13

AI Training & Enablement

Generic courses teach theory. Neume embeds AI literacy directly into your workflows, creating internal AI champions who drive adoption long after the engagement ends. Your people stop fearing AI and start leveraging it -- within weeks, not quarters.

Read the brief

14

Custom LLM Fine-Tuning

Neume Labs builds fine-tuned LLMs that speak your industry's language -- from legal clause interpretation to medical coding taxonomy -- delivering measurably higher accuracy, lower inference cost, and full data sovereignty throughout the training lifecycle.

Read the brief

Not sure which one?

If the work runs on documents, decisions, and handoffs, one of these applies. The audit tells you which to build first.

Book a call with an engineer

06Engagement shapes

Monthly. Scale up or down each month.

No minimum term. The shape is agreed on the call and can change as the roadmap does.

Two days a week

Fractional

One engineer, part time, one workflow at a time. The right shape for a 50 to 200 person company taking its first system into production.

Talk about this shape
One full-time engineer

Embedded

One engineer inside one department, shipping a system every four to six weeks and training the team that runs it.

Talk about this shape
Two to three engineers and a lead

Pod

Several departments at once, with a lead who owns the roadmap across them. For companies that want to move up the ladder fast.

Talk about this shape

07Built for companies that cannot get this wrong

Your data. Your infrastructure. Your repository.

Four guarantees, in every contract, before any system goes live.

Human in the loop

Every system ships with a review layer your team controls. It starts at 100% human review and falls as the system earns trust. By month six most clients run 85 to 90% autonomous, with humans on the edge cases.

100% audited outputs

Data sovereignty

Your data stays on your infrastructure and never trains public models. SOC 2 Type II, with every access, inference, and review logged and attributable.

0 data incidents

You own everything

Everything the engineer builds lives in your repository and runs on your infrastructure. Your people are trained to run it and extend it. Nothing walks out the door when the engagement ends.

Yours code and repository

Contractual KPIs

Processing time, error rate, cost per transaction, hours freed. Agreed before we build, reported monthly. If the return is not there, we tell you first.

Agreed before deployment

The window

Every week you wait, the gap compounds.

Productivity is 3.2x at month three and closer to 8x at month twelve, because the systems learn from every transaction and the people learn alongside them. A competitor starting from zero a year from now faces the same six-week build. They are twelve months of institutional learning behind, and that gap does not close.

Book a call with an engineer

30 minutes. An engineer, not a salesperson.
Or forward this page to your CEO.

rohan@neumelabs.ai