LR/AI

Technology services sales

Win complex deals with more capacity, consistency, and continuity.

Improve the workflows that connect sellers, solution teams, specialists, pricing, approvals, and delivery across complex pursuits.

Who this is for

Teams selling complex technology services where winning the deal depends on more than the seller.

This is built for technology services companies, typically around 25 to 500 employees, selling large, complex professional services deals to other businesses. The work is often $100K or more, involves non-standard services, and depends on coordinated input from account executives, sales engineers, specialists, pricing, delivery, and leadership.

The buyer is usually a CRO, VP of Sales, owner, or CEO who sees good people working hard but knows too much pursuit capacity is being lost to preparation, rework, inconsistent execution, and handoffs.

What we see

Your people are not the problem. The workflow between them is.

Sellers, solution teams, specialists, pricing, and delivery already know their jobs. The friction appears between people, systems, decisions, and handoffs, especially when the pursuit gets large or complex.

01Complex $100K+ pursuits consume seller and presales capacity
02Multiple stakeholders create gaps in context, decisions, and ownership
03Delivery and project risk can determine whether the deal is won
04The best pursuit method often lives in a few people and does not scale

Business impact

What business outcome would solving this drive?

The target is not “use more AI.” It is a measurable improvement in the way complex work moves from pursuit to delivery.

Proposal effort

Less time preparing, assembling, and reviewing complex proposals

Pursuit capacity

More active opportunities handled without adding headcount

Rework

Fewer approval loops from missing context, scope gaps, or inconsistent inputs

Time to decision

Less avoidable delay between serious buyer engagement and a decision

Sales-to-delivery continuity

Fewer commitments, assumptions, and client outcomes lost at handoff

Examples from prior internal work

Less delay. More capacity.

AI-enabled sales and presales workflows built and deployed inside B2B technology companies before this firm was launched.

FASTER PROPOSAL REVIEW
>80%
less review time

Reduced internal delivery-review time before proposals went to buyers.

MORE PROPOSAL CAPACITY
4+ hrs
saved per proposal

Proposal throughput increased more than 70% year over year at flat headcount.

How we approach the work

Start narrow. Define success. Prove value.

The goal is to make the first engagement clear to buy, bounded to deliver, and easy to judge on its results.

STEP 01
Pick the bright spot

Choose one economically meaningful workflow problem that is narrow enough to improve quickly and measurable enough to prove.

STEP 02
Define the work

Use a short discovery to agree on the deliverable, client inputs, timing, acceptance criteria, and fixed price before execution.

STEP 03
Build the smallest useful capability

Create something real enough to use in the workflow, not a strategy deck or another platform to manage.

STEP 04
Test and validate

Use representative work to confirm the capability meets the agreed acceptance criteria and improves the target metric.

STEP 05
Iterate from evidence

Expand only when the first improvement demonstrates value and the next step is worth pursuing.

Start here

Where is friction slowing your team down?

Start with the workflow, define the outcome, then decide where AI can help.