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ArtificialIntelligence

XERXES EngineeringPilot to production Typical timeline • 4–12 weeks
A processing core turning scanned documents into structured records

Most AI projects fail somewhere between the demo
and the Tuesday after launch. The demo runs on
twenty clean examples. Production runs on a
decade of scanned invoices, inconsistent naming
and the one supplier who still faxes. The gap is
where the work actually is.

We start from a job somebody is doing by hand
and measure what it costs today, so there is a
number to beat rather than a feeling that things
ought to be faster.

A model that is right most of
the time is not a feature. It is
a feature plus somewhere to
send everything else.

Document extraction, classification, matching and
routing are where we see the clearest returns,
because the input is messy, the volume is high
and the rules are already known.

The work runs on your data, and we hand over
the prompts, the evaluation set and the
thresholds, so what you end up with is a
system you own rather than one you rent.

GET STARTED

Ready when you are.

Tell us which job is eating hours and
we’ll scope it on a call — no obligation.

Book a Discovery Call

Service Mapping

  • Document and
    invoice extraction

  • Classification and
    routing

  • Data matching and
    deduplication

  • Workflow
    automation

  • Search over your
    own documents

  • OCR for scanned
    and photographed

  • Confidence scoring
    and thresholds

  • Human review
    queues

  • Integration into
    existing systems

  • Measurement against
    the manual baseline

BENEFITS

Why ChooseOur Solution

Measured against the job
somebody does by hand
today, not against a demo.

  • Accuracy reported

    Live accuracy is reported on the
    same measure after launch as
    before it, so a model that drifts
    shows up as a number.

  • Built on your
    real data

    Pilots run against your actual
    documents, including the bad
    scans and the odd supplier,
    because a model that only
    handles clean inputs fails in
    week one of production.

  • A review path

    Confidence thresholds and a
    human queue for anything below
    them. Nothing silently guesses
    and writes a wrong number into
    your ledger.

  • It lands in the
    systems you use

    Output goes into your ERP, your
    database or your workflow, not
    into a separate tool somebody
    has to check and copy from
    every morning.

  • We say when not to

    Plenty of problems are better
    solved with a rule, a form or a
    database query. We would rather
    say so than sell you a model
    that needs minding forever.

  • Pilot first,
    production second

    A scoped pilot with a clear
    measure comes before any
    commitment to a production
    build, so you can stop after
    the pilot without having spent
    the whole budget.

WHAT’S INCLUDED

  • A measured baseline before we start

  • Pilot against your real data,
    not sample documents

  • Confidence thresholds and a
    human review queue

  • Output written into the systems
    you already use

  • Accuracy reporting after
    go-live, not just before

OUR PROCESS

How wework

From a job done by hand to something measured and live.

  1. 01

    Baseline

    We measure what the manual process costs you today.

  2. 02

    Pilot

    A scoped trial on your real data, with a number attached.

  3. 03

    Decide

    You see the pilot result before committing to a build.

  4. 04

    Build

    Production pipeline, thresholds and the review queue.

  5. 05

    Measure

    Accuracy reported after go-live, and tuned as volume grows.