01 · The delivery feed

Your next feature in your software. Before your next meeting.

Every feature our agentic delivery team finishes for a client gets posted here the same day, with the requirement it answered, the stack it touched, and the clock that ran while it was built. Not a roadmap. A shipping log.

4h 03m

Median build time, requirement accepted to deployed in the client's testing or production system

Client features delivered in the last seven days, across 11 accounts

140+

Business platforms under management, the stack you already run

Change orders raised against any delivery on this page

Book a 30-minute call →Want this cadence in your stack? Bring one item from your list to the call.

Automated

Every post on this page is drafted and submitted for review by our agentic delivery system the moment a build closes.

Human-reviewed

Nothing goes live until a named member of our delivery team reads it and approves it. Humans hold the publish button.

Secure container

All development and data work runs inside an isolated VM container scoped to that one delivery. The container is destroyed when the work completes.

Consented

Each client has granted written consent to publish the delivery. We post the work, never the name.

Redacted

Company names, object names, field labels, record volumes and any identifying detail are stripped before review.

02 · ShippedShowing every delivery from the last two business days

Thursday, 17 September

3 DELIVERIES · 9h 40m ON THE CLOCK

1h 57m

On the clock

Start13:20

End15:17

RefCN-0917-01

Client type

Specialty retail

~90 employees · 4 warehouses

Supply chain

Reorder guardrail that stops a buyer over-committing cash

Reorder suggestions ignored open purchase commitments. An agent now checks committed cash and inbound transfers before a PO can be raised.

SHPShopify PlusNSNetSuite5TFivetran

The outcomeFirst 12 months

This is a cash-protection feature, not a growth one. Two working-capital breaches in eleven months were costing more in facility fees and scramble than the whole build.

Working-capital breaches since go-live

Two breaches in the prior 11 months, reconstructed from the ledger

$312k

Cash held back from early commitment

Nine POs trimmed in the replay, at the client's own landed cost

1h 40m → 4m

Buyer time per reorder review

Timed across four buyers in the first two weeks live

Speed/5

Reorder review drops from an afternoon task to a glance

Cost/5

$312k of cash uncommitted plus the avoided facility draw

Revenue/5

Indirect — stock mix improves, no new demand created

Time/5

≈640 buyer hours removed over 12 months

Impact scored 1–5 by our delivery team against the client's own baseline, taken from the systems named above. Source: client purchase ledger, 11-month replay

Book a 30-minute call →Approved and deployed to Production Org · replayed on 11 months of history

3h 31m

On the clock

Start09:02

End12:33

RefCN-0917-03

Client type

B2B software

~340 employees · ARR mid-eight figures

Revenue operations

Renewal risk brief that lands in the CRM before the QBR

CSMs were building renewal decks by hand from four systems. An agent now writes a sourced one-page risk brief onto the renewal opportunity 14 days out.

HSHubSpotSNWSnowflakedbtdbtCLClaude API

The outcomeFirst 12 months

The brief was never the point — the renewal was. Consistent, sourced risk two weeks out is what turns an at-risk renewal into a saved one, and it costs the CSM nothing to produce.

6.5 hrs → 0

CSM prep hours per renewal

40 renewals per quarter at the team's own logged prep time

+3.1 pts

Gross renewal-rate lift, at-risk cohort

Backtest across 60 closed renewals; at-risk accounts only

1,040 hrs

CSM hours returned per year

160 renewals × 6.5 hrs, from the CRM activity export

Speed/5

Risk surfaces 14 days out instead of the day of the call

Cost/5

No headcount change — prep time moves to account work

Revenue/5

3.1 points of renewal rate on the at-risk cohort

Time/5

1,040 CSM hours removed over 12 months

Impact scored 1–5 by our delivery team against the client's own baseline, taken from the systems named above. Source: client CRM activity export and the 60-renewal backtest

Book a 30-minute call →Deployed to Testing Org · backtested on 60 renewals

4h 12m

On the clock

Start08:14

End12:26

RefCN-0917-04

Client type

Industrial manufacturing

~1,200 employees · 6 plants

Quote-to-cash

Approval-routing agent that clears stalled quotes inside an hour

Quotes above a discount threshold sat in a manager's inbox for days. An agent now assembles the approval packet, routes it by delegated authority, and escalates on an SLA timer.

SFSalesforce CPQSLSlackAWSAWS LambdaFLFlow Orchestration

The outcomeFirst 12 months

Approval queue time was the binding constraint on collected cash. Removing four days from it moves quoted revenue into the quarter it was raised in and hands eight managers their Friday back.

4.2d → 51m

Median time to a cleared approval

1,140 approvals, 90 days before vs 30 days after go-live

$1.9M

Quoted value clearing in-quarter

Client's own $14.6M annual discounted-quote volume at the observed close-rate lift

2,080 hrs

Approver hours returned per year

8 approvers × 5 hrs/week of packet assembly, per the client's time study

Speed/5

4.2 days of queue time removed from every discounted quote

Cost/5

≈$214k of approver time redeployed rather than cut

Revenue/5

$1.9M of quoted value lands in the quarter it was raised

Time/5

2,080 approver hours removed over 12 months

Impact scored 1–5 by our delivery team against the client's own baseline, taken from the systems named above. Source: client approval log and Q2 time study, re-measured before release

Book a 30-minute call →Approved and deployed to Production Org · no change order

Wednesday, 16 September

3 DELIVERIES · 14h 37m ON THE CLOCK

5h 44m

On the clock

Start10:05

End15:49

RefCN-0916-02

Client type

Utilities contractor

~600 employees · 140 vehicles

Field service

Dispatch rebalancer that re-cuts the day when a tech calls out

One call-out used to cost a dispatcher an hour of re-sequencing. An agent now proposes a rebalanced board in under a minute, with SLA breaches ranked.

D365Dynamics 365 Field ServiceTWTwilioAZMAzure Maps

The outcomeFirst 12 months

A call-out used to cost a dispatcher an hour and the company an SLA credit. The rebalance proposal converts that hour into a decision and keeps the credit register near zero.

58m → 4m

Dispatcher rework per call-out

Median across a 40-day historical replay

$640k

SLA credits avoided per year

Client's 2025 credit register against the breach rate in the replay

97%

Call-out days rebalanced with no breach

40-day replay, 140-vehicle board

Speed/5

A rebalanced board in under a minute instead of an hour

Cost/5

$640k of SLA credits avoided over 12 months

Revenue/5

Recovered capacity covers ≈310 additional jobs a year

Time/5

≈1,150 dispatcher hours removed over 12 months

Impact scored 1–5 by our delivery team against the client's own baseline, taken from the systems named above. Source: client dispatch log and 2025 SLA credit register

Book a 30-minute call →Deployed to Testing Org · replayed on 40 call-out days

2h 48m

On the clock

Start08:40

End11:28

RefCN-0916-05

Client type

Regional insurance carrier

~2,400 employees

Claims operations

Duplicate-claim triage that runs before an adjuster opens the file

Adjusters were reconciling duplicate submissions by hand. An agent now clusters likely duplicates on intake and attaches the evidence for a one-click merge.

SNServiceNowSNWSnowflakePYPythonAZAzure Functions

The outcomeFirst 12 months

Duplicate pairs were being reconciled twice — once by each adjuster who had the file. Clustering at intake is an expense and accuracy play with a hard regulatory constraint on automation.

31m → 2m

Adjuster time per duplicate pair

Timed on 120 pairs across three intake channels

$486k

Loss-adjustment expense avoided per year

4,300 duplicate pairs/yr at the carrier's blended adjuster cost

94%

Duplicate precision at the agreed threshold

Measured against 900 labelled historical duplicates

Speed/5

Duplicates are clustered before the file is ever opened

Cost/5

$486k of loss-adjustment expense avoided

Revenue/5

No revenue effect — expense and accuracy only

Time/5

≈2,080 adjuster hours removed over 12 months

Impact scored 1–5 by our delivery team against the client's own baseline, taken from the systems named above. Source: carrier claims warehouse and the 900-claim labelled set

Book a 30-minute call →Approved and deployed to Production Org · merge remains a human action

6h 05m

On the clock

Start08:30

End14:35

RefCN-0916-01

Client type

Multi-site healthcare

~4,100 employees · 22 sites

Accounts payable

Invoice intake agent that codes to the right cost centre first time

AP was keying vendor invoices from PDFs and miscoding across sites. An agent now extracts, codes against the site's own history, and queues only what it is unsure about.

NSNetSuiteADIAzure Document IntelligencePAPower Automate

The outcomeFirst 12 months

AP was paying twice for every invoice: once to key it, once to correct the coding. Grounding the suggestion in each site's own history is what made first-pass accuracy hold across 22 sites.

6.4m → 40s

Handling time per invoice

Timed on the 400-invoice holdout set

$418k

AP labour and late fees avoided per year

96,000 invoices/yr at loaded coding cost plus the 2025 late-fee register

94%

First-pass coding accuracy

400-invoice holdout against the AP team's own answers

Speed/5

Invoices clear the mailbox the day they arrive

Cost/5

$418k of labour and late-fee exposure removed

Revenue/5

No revenue effect — early-pay discounts are the only upside

Time/5

≈8,900 AP hours removed over 12 months

Impact scored 1–5 by our delivery team against the client's own baseline, taken from the systems named above. Source: client AP ledger and the 400-invoice holdout

Book a 30-minute call →Approved and deployed to Production Org · 400-invoice holdout test

Durations are measured by our delivery platform from requirement acceptance to deployment in the client's own testing system, or to their production system where the delivery was approved for release. Figures on this page are unrounded. Ask us to walk one through live →

03 · Your turn

Bring your list of features that are behind on delivery. Let us show you how many we can deliver this week.

A 30-minute call. You bring your list of features and requirements. We price it, name the software platforms, and give you a delivery schedule for each item.

Book a 30-minute call →