FROM AI PRESSURE TO

Commercial
Advantage

Most companies deploy AI to cut costs. We help CEOs change what they sell, to whom, and at what price.

The commercial gap

AI investment underperforms when the commercial model lags

Four commercial leaks—not model performance—usually explain why.

L01

Pricing misaligned

Per-seat and per-license models capture less value than AI delivers—so product improvement can leave revenue behind.

L02

Invisible in AI search

Buyers shortlist vendors in ChatGPT, Perplexity, and Gemini. If your brand is absent, the decision starts without you.

L03

Long tail uncovered

Reps chase familiar accounts while lower-tier opportunities that AI could reach economically remain untouched.

L04

Expertise unproductized

Knowledge is still sold hour-by-hour while AI-native competitors package comparable expertise as a scalable product.

START HEREWhich of these four is costing you the most revenue right now?
Why internal attempts fail

AI stalls before revenue when commercial ownership is missing

Technology moves; pricing, coverage, incentives, and P&L ownership do not.

AI CAPABILITYinstalled
COMMERCIAL OWNERSHIPmissing

System integrators sell technology.
We lead the model change that makes it pay.

01

Technology-led

IT and R&D produce tools that do not command a premium or solve a paying customer problem.

02

Bolted onto broken processes

AI adds micro-productivity; revenue requires end-to-end workflow redesign and commercial choices.

03

Pilot purgatory

No one owns the P&L impact—or the pricing, coverage, and incentives that make the model stick.

04

Pricing conversation avoided

Sales, finance, and legal need alignment, but no internal leader has the mandate and distance to force it.

The revenue equation

Four levers act on one revenue identity

Start with any lever; the CEO conversation still resolves into one coherent commercial plan.

REVENUE = DEMAND CAPTURED (L2) × COVERAGE & CONVERSION (L3) × PRICE REALISED (L1) + NEW LINES (L4)
L01

Pricing

CLIENT SIGNAL
Per-seat pricing; usage rises while revenue stays flat.
OPEN WITH
“If AI does the work of three users, what do you charge?”
12-MONTH PROOF
Value-based unit + rollout evidence.
L02

AI-era demand

CLIENT SIGNAL
Strong SEO; absent from AI-generated shortlists.
OPEN WITH
“Does ChatGPT name you for priority category prompts?”
12-MONTH PROOF
Rising AI share of voice + tracked pipeline.
L03

Sales coverage

CLIENT SIGNAL
Reps over-serve familiar accounts; the long tail stays untouched.
OPEN WITH
“What share of addressable accounts received a meaningful touch?”
12-MONTH PROOF
Tiered coverage + faster onboarding and cycle times.
L04

Productisation

CLIENT SIGNAL
Deep expertise is still sold only by the hour.
OPEN WITH
“Which 20% is repeatable—and could sell without you?”
12-MONTH PROOF
One productized offer past MVP—or a clear no-go.
FOUR LEVERS · ONE P&L LOGICChoose the lever with the shortest path to proof.
Where to start

The fastest proof does not always carry the biggest upside

Pricing and sales coverage prove earlier; productisation is the larger, longer bet. Choose by proof horizon, not ambition alone.

L1 · PRICING

Fastest hard evidence

Decision document in 6 weeks.

L3 · SALES COVERAGE

Fastest hard evidence

ROI proof in ~90 days.

L2 · AEO

Early signal ≠ revenue

Baseline in 4 weeks; commercial proof by month 6.

L4 · PRODUCTISATION

Biggest longer-term bet

Go / no-go in 6 weeks; revenue in 9–18 months.

Our positioning

AI pays when the commercial model changes—not when another tool ships

The work belongs in the CEO agenda: pricing, demand capture, coverage, and new revenue lines. We sit with the CEO, force the commercial choices, and make the economics legible.

Why Renew can lead it
01 · PRICING ECONOMICS

Leadbook

Built and sold consumption-based and API models—and knows where definitions break.

02 · ENTERPRISE ADOPTION

Eurobios

Took AI-adjacent products into blue-chip buyers—and knows what procurement accepts.

03 · BUYER-READY LOGIC

Acquisition positioning

Made commercial logic legible to the people who pay for it.

THE PROMISEFind the revenue your AI can generate—then build the commercial model to capture it.
The approach

Agree attribution before the pilot—or ROI becomes an argument

Diagnose the lever, redesign the model, prove the economics, then scale. Decision first → model second → evidence before rollout.

016 weeks

Diagnose

Audit where AI erodes margin, creates uncaptured value, and which revenue lever has the shortest path to impact.

DELIVERABLEBoard-ready decision document
0212 weeks

Redesign

Rebuild pricing, AI-era demand capture, sales coverage, or productized expertise around the chosen lever.

DELIVERABLEStress-tested commercial model
0390 days+

Prove & scale

Run one customer pilot or one quarter of controlled testing; measure against agreed rules and scale what works.

DELIVERABLEEvidence, then rollout
MEASUREMENT RULES AGREED UP FRONTEvidence first. Scale second.
Ways to work together

Start with a bounded decision; scale to operating ownership

Fixed-fee diagnostic first; outcome-linked components where appropriate.

OPTION A

Revenue Lever Diagnostic

6 WEEKS

Identify the AI revenue lever with the fastest path to impact, with a quantified business case and go / no-go recommendation.

BEST FORCEOs who know AI matters but do not know where the money is.
OPTION B

Commercial Model Redesign

6 MONTHS

Take one lever end to end—pricing, demand capture, sales coverage, or expertise productization—through pilot validation.

BEST FORCompanies with AI capability that is not converting to revenue.
OPTION C

Fractional CEO / Transformation Lead

6–18 MONTHS

Own the P&L and lead the transformation on the ground, including exit or capital-raise preparation.

BEST FORBoards that need execution, turnaround leadership, and exit readiness.

Book a 30-minute diagnostic

Operator proof

The proof spans turnarounds, scale, and completed exits

2×EBITDAin 18 months
8×REVENUEto US$120M
2EXITSLeadbook + EuroBios
US$1BPIPELINEand US$120M ARR

Transformations & exits


  • Magellan X Group — doubled EBITDA, led a 150-person transformation, and repositioned the BCG/MISC/PETRONAS JV for acquisition by its largest customer.
  • Leadbook — built the commercial SaaS business, designed consumption/API economics, and sold it to a U.S. acquirer.
  • EuroBios — turned a 15-person R&D team into a viable AI-derived technology business; won BP, Ocado, and Unilever; then exited.

Scale, IPO & capital


  • Proxim Wireless — grew revenue eightfold to US$120M in five years.
  • ServiceSource — led the 3,000-person APJ organization toward a Nasdaq IPO, a US$1B pipeline, and US$120M ARR.
  • Raised capital, ran M&A and due diligence, and closed legal entities across Europe, Asia, the Middle East, and North America.
WHY IT MATTERSA rare combination: doubled EBITDA, two exits, and public-company scale.
Basheer Eric Cassim
Executive profile

Basheer Eric Cassim

CEO · GROWTH · TRANSFORMATION · TURNAROUNDS · SAAS · INDUSTRIAL IoT · TECHNOLOGY ENABLED SERVICES
  • Proven leadership — 25+ years progressing from financial roles to commercial roles and then enterprise leadership across Europe, APAC and the Middle East.
  • Commercial impact — Turning complexity into recurring revenue: doubled ARR and EBITDA at Magellan X, grew Proxim Wireless eightfold to US$120M, and ServiceSource’s APJ business to US$120M ARR.
  • Capital & investors — Led 12 rounds of capital raise, 4 acquisitions, 3 successful exits and helped build ServiceSource APJ to its Nasdaq IPO. Expertise in M&A and restructuring—due diligence, divestitures, acquisitions, and investor management.
  • Operational depth — Operator-led growth, pricing, go-to-market, recurring revenue and AI-enabled commercial models. Building teams that can execute.

MBA, London Business School · MSc Finance, Paris Dauphine–PSL

Next step

Book a 30-minute AI revenue diagnostic

In 30 minutes, we will
01

Identify which of the four revenue levers is most exposed—and most available—in your business.

02

Give you a preliminary view of the fastest path to measurable impact.

03

Agree whether an Option A diagnostic is worth doing.

Book your 30-minute diagnostic

The risk is not whether AI works. It is whether competitors redesign the commercial model first.