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Solutions · Intelligent Automation

More time for the work only your people can do.

Teams and AI systems working as one, so the organization does more.

Reading, extracting, re-keying and writing up. We move the repetitive work to AI and keep your experts on the judgment only they can make, so growth does not have to arrive as headcount.

Published work in drug discovery, lithium exploration, payroll software and game production.

Talk to us about throughput See the results
Client results

Manual work, taken out.

Each result below comes from the client's published case study.

Figures as published in each client's case study.

Why it matters

Our best people spend their days on work nobody chose to do.

The organization does more when people and AI work as one team.

Every business carries work that exists only because systems do not talk to each other. Someone reads a report to find three numbers. Someone re-keys a document into a second system. Someone writes up what changed after it already shipped.

None of it is anyone's fault. It is the shape of the process. When volume grows, that work grows with it, and so does the team. We've seen the largest gains come from taking the work out at its source, with AI reading and drafting and people reviewing, rather than asking the same team to go faster. Each person ends up with AI that reads, drafts and checks alongside them, and the whole team's output rises, not one person's.

  • Manual extraction
  • Re-keying between systems
  • Documentation behind the product
  • Volume tied to headcount
What you're hearing

The words that come before this work.

  • We need to do more with the team we have.

    Growth targets are rising faster than the hiring plan.

  • Our experts spend their days on data wrangling.

    Scarce specialists are doing work a model could do.

  • Productivity has to show up in the numbers this year.

    Leaders want efficiency they can see in cost to serve.

  • Turn times are too long.

    Work waits in queues between people and systems.

How value is earned

Effort removed is the first measure. Margin is the one that matters.

Use case

Extract fields from a report. Draft an article. Generate an asset.

tied to an outcome before anything is built

Outcome

Volume per person. Cost per transaction. Cycle time. Margin.

What we measure

  • Effort per task, measured as the work runs today
  • Volume handled per person, before and after
  • Cycle time from intake to done
  • Rework and error rates
  • Cost per transaction or per case

Finance signs the baseline before the first experiment. We report effort removed where that is what the evidence shows, and margin where finance can trace it.

What we build

Read, harmonize, draft and a person reviews.

Today
  1. Sources
  2. Read
  3. Structure
  4. Draft
  5. Review
With AI
  1. Sources
  2. Read
  3. Structure
  4. Draft
  5. PersonReview

The reading, keying and checking move to software. The judgment stays with your people.

  • Read at scale

    Document and vision models pull the facts out of reports, forms and images.

  • Harmonize

    Extracted data lands in one shared format your systems and teams can use.

  • Draft and generate

    AI writes the record, the article or the asset, to your standard.

  • Review and approvePerson

    A person approves before anything is used or published.

Document AI, Vertex AI, BigQuery, Claude, Stable Diffusion.

Control

Automation you can audit.

  1. 01

    Review stays human.

    AI drafts. A named person approves before anything is used or published, as on Avanti's release pipeline.

  2. 02

    Grounded in the source.

    Every extracted value points back to the document it came from.

  3. 03

    Checked for anything private.

    Drafts are screened before they leave the workflow.

  4. 04

    Quality measured, not assumed.

    Evaluations run against a sample your experts have checked by hand.

  5. 05

    Stop rules agreed up front.

    Each workflow has a budget, a time box and a stop rule before it starts.

Who's in the room

Your people and ours, one outcome.

You bring
  • the COO or function head who owns the cost line
  • the experts whose time is being freed
  • the owners of the systems the work runs through
  • a finance sign-off on the baseline
CWX brings
  • Data AI/ML with AI Engineering
  • the Transformation Office for AI enablement, so the teams whose work changes are trained and ready
  • evaluations and runbooks
Daniel JoanesSr. Director Data and AI

Leads Data AI/ML: data strategy, one shared meaning for your data, and the models built on it.

Data AI/ML
Industries

Where we work.

Health and life sciences

More time on discovery, less on data wrangling.

ProofDeepCure

Manufacturing and natural resources

50,000 reports read by models, not by hand.

ProofLilac Solutions

Technology and software

Documentation that ships with every release.

ProofAvanti Software

Media and gaming

More assets, at lower cost, in the pipeline you already run.

ProofKabam
Questions

Frequently asked questions

Something else on your mind? Ask us directly

  • It replaces the repetitive part of their work. Judgment and approval stay with them.

Get started

Put your experts on the judgment only they can make.

Tell us the task that eats the most expert time. We will show you what AI reads, what it drafts and where your people stay in charge.

Start the conversationTalk to us about throughputGo furtherRead the Lilac Solutions story

Prefer email? sales@cwx.tech