VERAPLOT

Automation & internal tools

Automation and internal tools to replace costly SaaS

Veraplot automates repetitive business processes and builds internal tools on AWS, often replacing SaaS subscriptions billed per seat. We write the logic in Python, run it on AWS Lambda and Step Functions, trigger it from schedules, file drops or events, and add a Next.js back-office wherever a person needs to check or approve. Each automation is a fixed-price deliverable, and the code runs in your account with no licence to renew.

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  • No per-seat bill

    You pay AWS for the seconds the code actually runs, not a monthly fee for every colleague who needs access.

  • Runs while you sleep

    Scheduled, event- or file-triggered flows with retries and alerts. Someone is notified when a run fails, not when a customer complains.

  • Built around your process

    The tool follows how your team really works, instead of your team bending to a generic product's screens and limits.

What you get

  • Process map and automation spec

    The current manual flow, the target flow, the edge cases and the human approval steps, agreed before any code is written.

  • Automated workflows

    Python functions on Lambda orchestrated by Step Functions, triggered by EventBridge schedules, S3 file drops, inbound emails or API calls.

  • Back-office web app

    A Next.js interface with sign-in, roles and an audit trail, for the steps where a person must check, correct or approve.

  • Generated reports and files

    Excel, CSV, PDF or JSON outputs produced on schedule and delivered by email, SFTP or SharePoint, or pushed straight into the next system.

  • Monitoring and handover

    Failure alerts, a run history anyone can read, infrastructure as code and a walkthrough so your team can extend it.

The stack

Picked for your context, not for a partner badge. Open formats first, managed AWS services where they pay for themselves.

  1. When

    Schedules, file drops, events and webhooks

    • Amazon EventBridge Scheduler
    • Amazon S3 event notifications
    • Amazon API Gateway
    • Amazon SES

  2. What

    Business logic in plain, tested Python

    • Python
    • AWS Lambda
    • pandas
    • Polars
    • openpyxl
    • Amazon Textract

  3. In what order

    Multi-step flows with waits, branches and retries

    • AWS Step Functions
    • Amazon SQS
    • Amazon DynamoDB

  4. Who checks

    A back-office for the human steps

    • Next.js
    • React
    • Amazon Cognito
    • AWS Amplify

  5. What if it fails

    Alerts, logs and one-click replay

    • Amazon CloudWatch
    • Amazon SNS
    • AWS X-Ray
    • Dead-letter queues

Typical use cases

  • Replacing a costly SaaS

    An internal workflow previously run on a per-seat SaaS, rebuilt as a serverless application with a Next.js back-office, owned and hosted by the client.

  • File-drop processing

    Supplier or partner files dropped on S3 or SFTP are validated, reformatted and loaded automatically, with rejected rows returned to the sender and logged.

  • Scheduled reporting

    Weekly Excel and PDF reports assembled from several systems and emailed to managers, replacing recurring manual copy-paste between spreadsheets.

  • Nightly reconciliation

    Records from ERP, CRM and spreadsheets matched every night, with discrepancies listed in a review screen instead of discovered at month-end close.

From first call to production

  1. 01

    Discovery call

    We map your systems, constraints and the outcome that matters. You talk to the engineer who will build it, not an account manager.

  2. 02

    Fixed-price scope

    A written scope with deliverables, milestones and one price, agreed before any code is written. No day-rate meter running in the background.

  3. 03

    Build in short iterations

    Working increments every one to two weeks, demoed on your data in your AWS account. Course corrections happen early, not at the end.

  4. 04

    Handover and optional run

    Code, infrastructure as code, runbooks and a walkthrough with your team. Run it yourselves, or keep us on support month-to-month or on a 1–3 year plan.

Questions buyers ask

How much does an automation project cost?

Most automations are small fixed-price packages, scoped and priced before we start, so you can weigh the one-off cost against the time and licences saved. Running costs are paid to AWS on usage and, for typical back-office volumes on Lambda and Step Functions, they stay modest. Larger internal tools with several workflows are scoped in milestones.

How long does it take to automate a process?

A single well-defined flow, such as a file-to-system import or a scheduled report, typically takes one to four weeks including testing on real data. An internal tool with a web interface, roles and several workflows is a one-to-three-month project, delivered in iterations so the first flow is in daily use early on.

Why not use Zapier, Make or Power Automate?

For simple, low-volume connections they are fine, and we will tell you so. They become expensive and fragile as volumes, branching logic and per-user pricing grow, and your logic lives in someone else's platform. Code on AWS gives you versioning, tests, proper error handling and no per-seat cost, which matters once a flow becomes business-critical.

Who maintains the automation after delivery?

You can: you receive the code, the infrastructure as code, documentation and a handover session. If you prefer not to, we keep it running under a support plan, either month-to-month or on a one-, two- or three-year commitment at a discount, covering monitoring, fixes and small changes.

Can you automate work involving PDFs, emails and Excel files?

Yes, that is most of what we automate. Python reads and writes Excel, CSV, JSON and XML; Amazon Textract or an LLM on Amazon Bedrock extracts fields from PDFs and scans; an inbound email can trigger a flow. Anything uncertain is routed to a human review screen rather than guessed.