The Brillrec platform

From scattered records
to a close you can
stand behind.

Reduce repeated reconciliation work, keep outstanding items in view and bring the final position together for review. Matching, AI assistance and sign-off share the same workspace.

Explore the workflow
Explore the platform
01 / Matching workspace

Reduce the matching work.
Keep the position clear.

Match corresponding entries, group split payments and settlements, and keep amount differences visible. Explore the records and review history in this sample workspace.

Operating account

September 2026 · NGN
Review in progress
₦12,480,000.00
₦12,482,500.00
₦2,500.00
Interactive illustration with synthetic records. Select a tab to explore.
Matching rules and grouped transactions

Compare references, amounts, dates and names. Group matching handles split payments and settlements; reversals can be identified within each side.

Explained match suggestions

Review candidate records, confidence and reasons before confirming or rejecting. Matching does not remove an unexplained amount difference.

02 / AI-assisted. Finance-led.

Practical assistance.
At the points that take time.

Help with matching, unfamiliar files, open items and close commentary. Your team’s policies and review guide the work.

01 / Matching review

A reason to review.

Assess possible pairings among eligible unmatched records. Inspect the suggested counterpart and its reason alongside the source entries.

02 / Open-item assistance

More context for your investigation.

Explore possible counterparts, grouped amounts, charges, duplicates, reversals and timing differences within your imported records. Brillrec’s checks find patterns; AI can summarise them for your assessment.

03 / File mapping

Less time interpreting columns.

Ask AI to suggest the columns in an unfamiliar file. Suggestions are checked against file values; review the mapping and preview before continuing.

04 / Close commentary

A starting point for your summary.

Draft period commentary and a sign-off memo from the reconciliation figures. Check, edit and save the text for inclusion in the sign-off pack.

Inside matching review

See the records behind the suggestion.

Compare both sides and check the proposed reason. A suggested explanation is a starting point for review; your team establishes the cause and decides how to treat a difference.

How AI assistance fits your workflow

Your organisation chooses whether external AI is used and the review mode. Matching and approval settings govern eligible actions, while commentary and file mappings remain drafts for your team to check.

Open-item checks also work without external AI. Discuss data handling and provider requirements with us during evaluation.

Explore AI settings
An AI matching suggestion comparing two source records with its reason and decision controls
Inspect the candidate records and the reason for reviewing them.Sample records · Enlarge screenshot ↗

Fictional records and illustrative AI output.

03 / Imports, automation & learning

Turn approved decisions
into less repeated work.

Build on decisions your team has reviewed. Reuse familiar name links, prioritise suggestions using past decisions and review proposed rules for recurring differences.

A qualifying manual match can propose a name link. Your administrator accepts it before it is reused, with amount and date checks still applying.

Import and connect your records

Use CSV, Excel and PDF statement imports, or configured accounting, bank, SFTP and API sources. Review the interpretation and save layouts for repeat imports. AI can suggest unfamiliar column mappings, and connected sources can be reloaded to pick up late or backdated entries.

Explore source connections
Set conditions for automation

Account policies define confidence, amount limits and allowable differences for automatic matching. Choose whether AI review suggestions are eligible. Remaining differences still require an explanation.

Configured rules can handle recurring explanations. Daily checks are available for accounts with connected accounting and bank feeds. Open items carry into the latest period and stay in step with earlier periods as work progresses.

How approved learning carries forward

Accepted name links connect familiar customer names with bank narrations. Repeated explanations of similar charges or entries can propose difference rules for review. Confirmations and rejections help order future suggestions, and previously rejected pairings are remembered.

Approved learning stays within your organisation, with accepted links providing reusable context for future matching.

05 / Product preview & reports

A reconciliation
your reviewer can follow.

Inspect the financial position and the records supporting it: bank statements, settlement comparisons, investment schedules and client-money statements.

Open the product preview
The financial position

Statements and schedules.

Review adjusted bank balances, settlement records and investment comparisons. Client-money statements show the requirement, resources held and surplus or shortfall.

Explore client money ↗
The reviewer’s evidence

Sign-off packs.

Bring statements, supporting schedules and saved commentary into a PDF pack. Keep outstanding items and the decisions behind the close visible.

The working detail

Working papers and exports.

Use Excel working papers for reconciliation detail and balanced journal CSV exports with configured ledger codes. Export client-money statements as PDF or CSV.

Prepare your evaluation ↗
Your records. Your controls.

See the workflow
in your context.

Evaluate a representative workflow: bring in your records, inspect the matching and outstanding items, then review the resulting statement and evidence.

Try a guided reconciliation
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