Rukh Labs takes recurring spreadsheet, reporting, reconciliation, and migration processes off your team's plate—then adds the validation, exception handling, and monitoring needed to keep them trustworthy.
The offer is not “more dashboards” or “AI agents.” It is accountable ownership of one defined operating process and evidence that the output is right.
Synthetic workflow lab
Monthly operations close
Inputs
Messy source files
Controlled workflow
Automate the mechanics
Headers, types, dates, IDs
Deterministic rules first
Counts, totals, nulls, duplicates
Only unresolved exceptions
Outputs
Review only exceptions
12
mock source files
2,840
synthetic rows
37
flagged exceptions
100%
control totals matched
The expensive part is the brittle chain before the output: missing files, changing columns, duplicate records, unclear mappings, manual fixes, and no reliable way to prove the result.
People download, rename, combine, clean, and reshape the same exports every reporting cycle.
A source, column, credential, or gateway changes and the output quietly stops being trustworthy.
Teams compare old and new systems, chase missing records, and explain mismatched totals by hand.
Mappings exist in scattered spreadsheets, transformation rules are unclear, and sign-off lacks evidence.
One analyst knows the sequence, the exceptions, and the fixes. When they are unavailable, the process stalls.
A dashboard can look polished while duplicates, missing IDs, changed schemas, or bad totals go undetected.
This fictional workflow begins with inconsistent location files and a master reference list. It standardizes schemas, matches records, validates totals, and produces both a management output and a human-review queue.
The operating contract
Every expected file arrives. Every transformation is repeatable. Every control is recorded. Every unresolved record is visible. The final output is released only when the agreed acceptance rules pass.
All data shown in the demonstration is synthetic. It does not represent an employer, client, customer, or production environment.
Synthetic workflow lab
Monthly operations close
Inputs
Messy source files
Controlled workflow
Automate the mechanics
Headers, types, dates, IDs
Deterministic rules first
Counts, totals, nulls, duplicates
Only unresolved exceptions
Outputs
Review only exceptions
12
mock source files
2,840
synthetic rows
37
flagged exceptions
100%
control totals matched
Code is only one layer. The useful deliverable is a controlled operating system around the work, with explicit boundaries and evidence.
Inputs, transformations, matching logic, outputs, and human approval points are explicit instead of living in one person’s memory.
Row counts, control totals, schema checks, duplicates, nulls, and reconciliation results are recorded rather than assumed.
The routine work runs automatically. People review the records that actually require judgment or correction.
The handoff states how the process runs, what is monitored, what triggers escalation, and what remains a client decision.
Rukh Labs can work directly with an operations, finance, reporting, or data team to remove one recurring workflow and leave behind a controlled process instead of another fragile file.
Microsoft consultancies, MSPs, ERP or HRIS implementers, fractional CFO firms, and operations advisers can use Rukh Labs behind the scenes for Power BI, Power Query, reconciliation, mapping, and migration QA.
These are starting scopes. Final price reflects confirmed sources, data sensitivity, edge cases, deployment requirements, and support boundaries.
Fixed-scope emergency repair
From $395
Repair one broken workbook, query, refresh, reconciliation, report, or recurring file process without turning it into an open-ended consulting engagement.
A specific failure with a real deadline and a clearly bounded outcome.
Credited toward an approved implementation
$750
Map the process, identify failure points and wasted effort, define controls, and receive a fixed implementation scope instead of a vague discovery deck.
Recurring work that is painful but not yet cleanly scoped.
Fixed implementation scope
$3k–$10k
Turn one recurring spreadsheet, reporting, reconciliation, or file-handling process into a controlled workflow your team does not have to rebuild every cycle.
Weekly or monthly work that consumes hours, depends on one person, or fails silently.
Managed operation and monitoring
$750–$2.5k/mo
Keep an automated process healthy after launch with scheduled runs, failure monitoring, reruns, source-change repair, and small continuous improvements.
Teams that want an accountable owner instead of another unattended automation.
Source-to-target validation package
$5k–$15k
Create the mapping, transformation rules, reconciliation evidence, exception log, and sign-off package needed to prove a migration actually worked.
ERP, HRIS, CRM, BI, or reporting migrations where incorrect data is expensive.
Third-party platform, cloud, licensing, connector, and hosting costs are separate when required. Fixed scopes assume timely access to agreed sample data and decision-makers.
Start with the recurring output, deadline, source owners, manual effort, and cost of failure—not a preferred tool.
Identify schema variation, missing keys, duplicates, source drift, edge cases, and any security constraints before building.
Build ingestion, transformation, matching, reconciliation, exception routing, and output generation around a fixed scope.
Test known cases, compare totals, document exceptions, and establish acceptance evidence before the workflow is treated as complete.
Track missing files, schema changes, failed runs, duplicate spikes, reconciliation gaps, and required human approvals.
The form is designed to qualify the process without requiring a sales call, production access, or a pile of attachments. Specificity gets a better answer.
Security boundary
Do not submit credentials, personal records, confidential datasets, or production exports. The first step uses descriptions, redacted examples, or synthetic samples.
No. Power BI may be part of the solution, but the service is built around owning an operating process: collecting inputs, cleaning and matching data, validating totals, routing exceptions, producing the output, and monitoring what can break.
No. The first conversation should use a process description, redacted screenshots, sample layouts, or synthetic files. Secure access and data-handling requirements are agreed before any real data is transferred.
Yes. Rukh Labs can own a defined workstream, provide white-label delivery, or handle reconciliation and migration QA while another firm manages the broader implementation.
Typical work uses Excel, CSV files, Power Query, Power BI, SQL, Python, APIs, SharePoint, and exports from ERP, CRM, HRIS, finance, or operational systems. The tool is selected after the process and control requirements are clear.
Not by default. AI can accelerate profiling, code generation, documentation, and anomaly review, but deterministic controls, reconciliation rules, human approval points, and audit evidence remain the core of the delivery.
Unbounded staff augmentation, vague build-us-an-AI requests, unpaid discovery, projects requiring unauthorized access, or regulated production work without an agreed security and compliance path are not a fit.
Start with the process that costs the most time, creates the most risk, or depends on the most fragile chain of manual fixes.