Source and mapping reconciliation
Source and mapping reconciliation. Keep the source details and outstanding dependencies together.
SOURCE FEED / PIPELINE RUN / DATA CONTRACT
AI agent for data engineering consultancies
Keep every source change connected to a working data delivery.
Your AI agent handles source and mapping reconciliation and pipeline exception resolution.
A specialised AI agent you can ask for more. Chat here on the site.
$149.00/month, including $60.00 in monthly credits. Monthly subscription. Before tax.
Specialised AI agentYour own report presetNo connection needed to begin
Data pipeline coordinationSPECIALIST / 848
YOUR SPECIALISED AI AGENT
One place for source and mapping reconciliation, pipeline exception resolution, delivery checks and client reporting.
MADE FOR YOUR WORKDAYStart with work already on your desk
Your first useful assignment.
Share the relevant records in your regular Teams chat and give your specialist an outcome. No model or tool choices to make first.
Get my AI agent →YOU COULD ASK
“Take ownership of the client's daily data deliveries, resolve recurring failures and complete a documented recovery and prevention plan.”
- Source and mapping reconciliation
- Pipeline exception resolution
- Delivery checks and client reporting
A useful first result
An editable data pipeline coordination working register with traceable references, resolved discrepancies and specific next actions.
Example assignment, not a promised delivery time. Your agent works from the records and access you provide. Add connections when you want it to act in other systems.
A conversation at your desk
Take ownership of the client's daily data deliveries, resolve recurring failures and complete a documented recovery and prevention plan.
This example shows an established working setup: the agent already knows the business and has the records and connections listed below. Hand over the assignment and it carries the work through to saved results.
Illustrative project · configured agent at work
A configured agent with your source feed, pipeline run and data contract records, current commitments and the connected accounts used for pipeline exception resolution.
- Source and mapping reconciliation
- Pipeline exception resolution
- Delivery checks and client reporting
A working specialist can handle the project, with a configured team sharing the work where available. This is an example of what you can build up to, not a first-launch conversation. Timing and usage depend on the assignment.
- You · Data engineering consultancies
Take ownership of the client's daily data deliveries, resolve recurring failures and complete a documented recovery and prevention plan.
- Your AI agent · AI Agent Store
One source changed a field type and another feed arrived twice. I am correcting the affected mappings and tracing downstream duplicates.
Work in progress - You · Data engineering consultancies
Keep the agreed data contracts and verify the affected deliveries before closing the incident.
- Your AI agent · AI Agent Store
The corrected deliveries reconcile to their source batches, recurring failures have tracked fixes and the client dashboard distinguishes verified delivery from pending recovery. Your working files and dashboard reflect the recorded outcomes.
Later · delivery and saved results
SOURCE FEED / PIPELINE RUN / DATA CONTRACT
A working brief for your AI agent.
Track source schemas, transformation versions, freshness commitments and reconciliation rules. Diagnose failed jobs through actual logs, compare delivered records to agreed checks and preserve lineage; follow upstream changes into the affected downstream outputs. Your specialist maintains these working records in regular Teams as the assignment develops.
AI
Your AI agentPrepared for data engineering consultancies
Data pipeline coordination working registerEXAMPLE, NOT LIVE ACTIVITY
An example record for source feed, pipeline run, data contract, data deliveries verified.
01Source feed02pipeline run03data contract
The useful next step
Source and mapping reconciliation
Prepare source and mapping reconciliation from the available records. Save the supporting references and mark any missing details so the next step stays clear.
From enquiry to a useful next step
Data pipeline coordination working register. Your way of working.
01
Brief and source records received
Add a job reference and the details you already know.
02
Source and mapping reconciliation
Source feed and pipeline run, ready to check.
03
Pipeline exception resolution
Give your specialist the outcome and let it carry the work forward.
04
Outcome evidence verified
Keep working records in Files and Tasks.
05
Delivery checks and client reporting
Keep the job and its next steps together.
Ask your specialist to maintain your working records in Files and Tasks and adapt the reports in Teams Dashboards. These are the regular platform tools, prepared for your business. Connections to other systems are optional.
The details your specialist follows
Inside the data pipeline coordination
Follow each source feed through the working record. The example below shows how references, dependencies and resolutions stay together, so you can trace what changed and what happens next.
Keep an eye on: schema changes, repeated job failures and unverified backfills.
Illustrative working document · your records start empty
| Source feed | Dependency to follow | Evidence of completion |
|---|---|---|
| DATAENGI-104 | Source and mapping reconciliation | Pipeline discrepancies resolved |
| DATAENGI-118 | Pipeline exception resolution | Backfill cases closed |
| DATAENGI-126 | Delivery checks and client reporting | Delivered batches meeting data contracts |
Active data pipeline coordination records3
Data deliveries verified48 deliveries
Outcomes with supporting evidence2
Illustrative project figures. Your agent maintains working records in normal Files and Tasks and reports completed work in Teams Dashboards. Ask it to adapt those records and reports as your workflow changes.
Built around the details that matter
Source and mapping reconciliation. With the right questions already in mind.
For consultancies building and maintaining client data pipelines.
Pipeline exception resolution
Pipeline exception resolution. Track changes against the same job reference.
Delivery checks and client reporting
Delivery checks and client reporting. Save the outcome and carry the next steps into your working records.
A small tool for a real job
Delivery checks to coordinate. Before the back-and-forth.
Follow schema changes, repeated job failures and unverified backfills before they turn into another missed commitment.
Try the numbers, then bring the confirmed brief to your specialist. Start with a reference such as “Job 104”—you do not need to upload your customer database.
- Source feed
- pipeline run
- data contract
- Data deliveries verified
Try your own numbers
Delivery checks to coordinate
Planning arithmetic from your inputs. Your specialist can turn the confirmed details into a working brief. This is not a quote or capacity commitment.
Prepared for your business
The numbers behind your data pipeline coordination.
Six useful measures, ready in your regular Teams dashboard. Your specialist keeps them up to date from the real work and records it can access. Ask it to change a measure, add a report or investigate what is behind a result.
Recorded total · deliveries
Data deliveries verified
What this measures
Actual deliveries for data deliveries verified, from completed source records in the data pipeline coordination working register. Log the observed quantity once per source completion; exclude planned work, duplicate updates and example figures.
Recorded cases · cases
Pipeline discrepancies resolved
What this measures
Distinct pipeline discrepancies resolved cases supported by a recorded outcome in the data pipeline coordination working register. Count once per source case; repeated messages, reopened cases and routine checks are not additional completions.
Recorded cases · cases
Backfill cases closed
What this measures
Distinct backfill cases closed cases supported by a recorded outcome in the data pipeline coordination working register. Count once per source case; repeated messages, reopened cases and routine checks are not additional completions.
Average · hours
Failed delivery to verified recovery
What this measures
Elapsed hours for failed delivery to verified recovery, using actual start and completion timestamps for the same source case. One duration per completed observation; omit pending cases and missing timestamps.
Observed rate · %
Delivered batches meeting data contracts
What this measures
Delivered batches meeting data contracts divided by all completed assessments of the same requirement with a known met or not-met outcome. Use the agreed job specification and actual evidence; classify each source case once, excluding pending and unassessed work.
Observed rate · %
Agreed freshness windows met
What this measures
Agreed freshness windows met divided by completed commitments with known original agreed deadlines and actual completion timestamps. Record on-time or late once per commitment; exclude pending or undated work and never move a past deadline to hide lateness.
Your reports start empty. Figures reflect observed work in the selected period; missing records are not treated as measured zeroes. Current jobs, schedules and stock stay in your working files and tasks. You and your agent can adapt the dashboard as your business changes.
Keep the tools that already work
Specialised in your trade. Open to your next idea.
Your AI agent starts with the details of your business already in mind. The three workflows are starting points. Ask it for help with another task in the same conversation.
An AI agent prepared for your business
The starting instructions, intake questions and working rules already match data engineering consultancies. Add your service list and one example of your tone when you are ready.
Give your agent the whole job
Give your agent an outcome, the access it needs and your budget. It handles routine decisions and follows through in your connected tools, asking when a missing business decision needs you. Set or change your own boundaries whenever you want.
Ask beyond the starting workflows
Ask your data pipeline coordination to investigate recurring exceptions, compare suppliers, improve customer communications or take on another business assignment in the same workspace. Give your agent another task in plain language. What it can carry out depends on the tools you connect and the access you choose.
Recommended starting plan
Your AI agent for data engineering consultancies.
Begin with one specialist and a report preset for your business. After setup, your regular Agent Teams conversation opens. No tool selection before your first conversation.
$149.00/month
Capacity for 3 running agents · 250 active hours per month
Start my AI agent →A clear starting total
$149.00 before tax today and monthly, including $60.00 in Platform Credits after the first payment and each paid renewal.
Unused credits roll over. AI usage draws from your balance; additional credits are available when needed. $0.15 applies per active hour beyond the included allowance. Optional voice and other services cost extra.
Hosting availability is checked before payment. Create your account, confirm your monthly subscription, then start chatting when your specialist is ready. Your instructions and dashboard are prepared automatically after payment.
Automatic top-ups start off. Buy credits manually or set automatic top-ups and spending limits in your account. Keep the full Teams controls for models, connections and supported settings.
Before you begin
An AI agent for data engineering consultancies.
Can it follow source feed, pipeline run and data contract through the whole assignment?
Track source schemas, transformation versions, freshness commitments and reconciliation rules. Diagnose failed jobs through actual logs, compare delivered records to agreed checks and preserve lineage; follow upstream changes into the affected downstream outputs. Start with the records you have; add connections when you want it to work in those systems.
Is this only for the three tasks shown?
No. This is an AI agent specialised for data engineering consultancies, with three prepared workflows to get you started. You can ask for writing, research, planning, analysis or another task in the same chat. It can make routine decisions and carry the work through using available tools. You set its boundaries; it asks when a real business decision or missing access needs you.
What happens after I subscribe?
After payment, we prepare your AI agent for data engineering consultancies, its workflows and your data pipeline coordination working register dashboard. Your regular Agent Teams chat opens when setup is ready. Files, Tasks, settings and billing work the same as for other customers. Reports start empty and count actual reported work; the examples above are illustrative.
Do I need to connect email or messaging?
No. Prepare your first brief and draft here. Connect external channels later when you want the specialist to work there.
Does this replace my existing business software?
Use it alongside your current tools for preparing work and organising jobs. Live stock, availability, sending and payment records require a verified connection or your own confirmation.
Choosing for a different business?
Compare the working records and business types each specialist is prepared for.
Explore AI agents for creative and digital services →