Less friction.More flow.

Monthly financial operations with dozens of entries in portals that require a form per item, cross-checking against a source document and individual accountability for whoever clicks “Submit”. A professional spends days filling in, checking and filing. A typo costs rework or rejection of the entry.

We’ve built a pipeline that does all the prep — it extracts the data from the source documents, fills in each form on the portal, captures the server’s canonical reference in parallel (exchange rate, protocol number, current index) and stops before submission. The window stays open for the specialist to review and confirm item by item, in the same session. At the end, another script files the documents in the format defined by the firm and consolidates the cycle’s ledger. The bot submits nothing. The final decision stays with whoever signs off.

• The cycle’s prep time drops from days to minutes; the review becomes focused and auditable.
• Rates and references come from the server itself — no discrepancy between what the specialist sees and what the system recorded.

Back-office operations that process a high daily volume of unstructured documents (reports, filings, client dossiers, complex records), with dense business rules and minimal margin for reading errors.

A three-phase flow. Collection: direct access to the sources via native integration where it exists; a custom HTTP client where it doesn’t — without relying on a headless browser. Parallel analysis: multiple specialist sub-agents read the same material on complementary fronts (key dates, applicable rule, identifiers, figures). Cross-validation: critical data is produced by at least two independent agents; discrepancies become a visual flag in the final artefact, never silence. Output in the firm’s standard template, with fields flagged for review whenever there’s doubt.

• Each piece is read in seconds, not minutes; the specialist receives the artefact pre-built and reviews what matters.
• The redundancy catches model hallucination and source discrepancy before the final product ships — “trust the quorum among LLMs”, not “trust the LLM”.

Each new web automation (filling in a portal, extracting data from a system with no API, validating an application flow the client built) tends to replicate expensive boilerplate: browser management, authentication that survives between runs, useful error capture for debugging, integration with a test runner.

We operate on a single internal hub that covers four modes of use on the same foundation: QA of pages the client develops, automated bug reproduction (red→green), scraping of third-party systems, and actions on systems that require login. Auth resolves via two paths selectable case by case — a full persistent real-Chrome profile when the site demands it (service workers, cache, login that survives), or a lightweight JSON session state when the site cooperates.

• The time between “we identified the problem” and “automation running in your environment” is shorter — we’re not reinventing infrastructure on every project.