For leadership teams at growth-stage and PE-backed companies

Better decisions. Real outcomes.

AI can draft a strategy in minutes, and so can your competitors. We bring the evidence, judgment and buy-in to choose the right one, then build, run and hand over the capability that delivers it.

Book a 30-minute conversation

No deck, no sales pitch. A working conversation about how to achieve results.

What we do

Pick where to start: AI productivity, GTM, product, or AI and data.

The problem

You don't need another strategy deck, tool, or AI demo.

If any of these sound familiar, you're in the right place.

01

Your team uses AI. The work hasn't changed.

Everyone has a copilot, yet decisions get relitigated, drafts revive options you already rejected, and context is rebuilt at every handoff.

02

Your GTM stack grew. Your pipeline didn't.

CRM, martech and salestech everywhere, yet deals stall, handoffs leak, and nobody trusts the numbers.

03

The roadmap is full. The growth story isn't.

Too many bets, no clear reason any of them wins, and pricing and packaging that lag the market.

04

AI pilots impress, then stall.

Without an owner, a baseline or usable data, nothing reaches operations, and the board wants results, not another roadmap.

The solution

We redesign the workflow, not just the tools.

You need a better way to run the work that delivers outcomes, with a team that can manage it. That’s where we start.

01Fixes: AI that hasn't changed the work

Team workflows on one shared context.

We redesign how your people and AI agents share the work, and keep current decisions, owners and reasons in teamctx. Every person and AI tool works from the same approved context.

Case study: improving decision quality (opens in a new tab)
02Fixes: a stack that doesn't move pipeline

One GTM system, from positioning to pipeline.

We connect positioning, pricing and the sales motion with the CRM, martech and data behind them, give each part an owner and a metric, and run it until pipeline moves.

Case study: they treated GTM like a product (opens in a new tab)
03Fixes: a roadmap without a growth story

Fewer, sharper bets, validated before you build.

We size the opportunity, set pricing and packaging, and test the bet with real customers, so the roadmap and the board plan tell the same story.

Case study: idea to board-approved launch in 14 weeks (opens in a new tab)
04Fixes: pilots that stall

Pilots built to become operations.

Design & Prove sets the baseline, owner, data and business case before anything is built. Then we run it on real work until the results hold, and hand it to your team.

Case study: 12 months of planning, down to weeks (opens in a new tab)
Why StatsLateral

We are senior operators obsessed with one thing. Outcomes.

Everything we do is built, run and measured against the result you set.

01

Results are the scorecard.

We agree the numbers first: revenue, cycle time, cost and decision quality. Not decks delivered or agents deployed.

02

Senior operators only.

Every engagement is led by people who have run product, go-to-market and P&Ls, so the plan reflects what it takes to deliver the result, not just present it.

03

We stay until it performs.

We build it and run it on real work through Operate & Optimize, so the capability delivers before it is handed over.

04

Ownership is explicit.

A named owner is accountable for each decision and outcome. Not a vendor, not an agent.

05

AI does the legwork. Your leaders make the calls.

AI handles research, analysis and coordination, and flags uncertainty instead of guessing. People keep the consequential decisions.

06

You end up not needing us.

Support is optional, never a condition for the results to keep coming.

How we work

Build → Operate & Optimize → Train & Transfer

Most firms stop at the handoff. We run the capability on real work until it performs, then make sure your team can run it without us.

Start here: Design & Prove

We pick one consequential problem, whether a GTM motion, a product bet or an AI workflow, measure how it runs today, and prove the approach on real work before you commit to the build.

1

Build

We design the capability and implement it in your business: a GTM system, a product and pricing plan, or an AI-enabled workflow. Clear owners and decision rights, built in your systems, with your data and constraints.

In practice: They treated GTM like a product. Then shipped it.

You getA working capability. Not a deck. Not a demo.
2

Operate & Optimize

We run it on real work alongside your team. We measure outcomes, find where it breaks, and tune responsibilities, approvals, quality, cost and controls until the results hold.

You getA proven capability with defined performance and economics.
3

Train & Transfer

We train the people accountable for it and hand over the playbooks, workflows, systems, integrations, SOPs and metrics, against handoff criteria agreed up front. For AI workflows, the decisions and context stay in teamctx, in your own repository.

You getA capability your team owns and improves without us.

The scaffolding comes down. Ongoing optimization is available if you want it. It's never required to keep the capability running.

Client impact

Outcomes, not output.

Proof, not promises. Our most recent client work, newest first.

Customer SuccessProfessional Services

Improving Decision Quality in AI-Enabled Product Teams

A leading global strategy consulting firm's teams had AI access to a year of project history, but not a reliable way to know which decisions still governed the work. Reusable AI workflows made decisions more consistent and reduced repeated review.

~50People, 10–15 teams
MoreConsistent decisions
LessRepeated review
Read full case study →
Customer SuccessApparel & Fashion

12 months of innovation planning, down to weeks.

A Fortune 500 apparel and lifestyle company benchmarked agentic AI against its own 18-month innovation process. A 40+ agent system, grounded in proprietary data, compressed roughly 12 months of planning and cross-functional coordination toward weeks — and leadership operationalized it.

40+Orchestrated agents
Months → weeksPlanning compressed
AdoptedInto the workflow
Read full case study →
Customer SuccessHealthcare Technology

18-month deals, closed in 6.

A healthcare platform cut enterprise cycles from 18 to 6 months and killed 90% of stalled deals with a three-role qualification framework.

18 → 6Months, sales cycle
90%Fewer stalled deals
StrongerStakeholder alignment
Read full case study →
Customer SuccessHospital Systems

The product was fundable. The story wasn't.

A hospital systems platform rebuilt its narrative into a Land → Expand → Deepen growth story and closed investor ambiguity across product, GTM, and financials.

1 MonthInvestor-ready
StrongerBusiness model
ImprovedInvestor engagement
Read full case study →

Industries we know

  • B2B SaaS
  • Martech & ad tech
  • Healthcare technology
  • Hospital systems
  • Fintech
  • Travel technology
  • Professional services
  • Real estate technology
  • Apparel & consumer goods

See all client stories →

How we engage

Clear scope. Your ownership. No lock-in.

Commercial terms

  • Fixed scope, milestone-billed. No hourly billing, no open-ended retainers.
  • Start small. Design & Prove on one problem before a larger commitment.
  • You own the result: playbooks, systems, workflows, SOPs and metrics.
  • Ongoing support is optional.

Trust and governance

  • People keep consequential decisions, with a named owner for each one.
  • Built in your systems, your CRM, data stack and tools, within your operating constraints.
  • Senior operators on every engagement, not junior teams learning on your budget.
  • No lock-in. You keep everything we build. The context layer we use is open source.

Working across jurisdictions? Read: The sovereignty tax

Open source

teamctx

AI-native version control for team context. The decisions, rules and assumptions behind the work, approved by the people accountable for them and available to every AI tool your team uses. It's how a handoff keeps its reasoning.

  • MIT licence
  • Git-backed
  • Manager-approved
  • CLI + MCP
View teamctx on GitHub →

PE operating partners: prove a capability in one portfolio company, then adapt it across the rest.

Latest thinking

What we're seeing in AI, SaaS economics and growth.

AI Can Read Your Files. Who Decides Which Ones Are Right? AI Strategy · Oct 29, 2026

AI Can Read Your Files. Who Decides Which Ones Are Right?

Access permissions determine what AI may read, not which business decisions are current, why they changed, or who owns them. Why decision ownership, supported by AI, is the operating fix.

 Can Claude or Copilot Bring Your Agency In-House? Marketing · Aug 26, 2026

Can Claude or Copilot Bring Your Agency In-House?

Only 12% of brands have AI fully integrated into marketing workflows. Why the real question isn't what to cut from agency scope, but which capabilities should become core — and the barbell reshaping agency fees.

 AI Made Building Easy. It Didn't Make Ownership Cheap. AI Strategy · Aug 17, 2026

AI Made Building Easy. It Didn't Make Ownership Cheap.

AI made building cheaper. It did not make ownership cheap. Why the real cost of enterprise AI sits across human oversight, orchestration, infrastructure and operations — and a framework for deciding what to build, buy, partner for or rent.

 The Sovereignty Tax: Why AI Is Rewriting the Economics of Global SaaS SaaS Economics · Aug 17, 2026

The Sovereignty Tax: Why AI Is Rewriting the Economics of Global SaaS

SaaS was built on pooling everything across one global deployment. AI and jurisdictional regulation just broke that premise — six sovereignty design levers, four hyperscaler bets, and the tiered architecture that turns the tax into a moat.
See all essays and case studies →

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Our team

Senior operators, not generalist consultants.

Shikhin Agarwal

Shikhin Agarwal

Founder & CEO
25 years in tech and AI platforms.
Former P&L Executive at VC-funded social media, ecommerce, fintech, digital healthcare, and consumer SaaS companies.

View profile →
Rajeev Singh

Rajeev Singh

Founding CTO, Advisor
25+ years in tech and AI
CTO at modern platforms, startups, e-commerce, fintech, AI, and blockchain.

Balaji Gopalan

Balaji Gopalan

CPO, Advisor
30+ years in tech, software and AI.
B2C and B2B across security, social, dev tools, edtech, martech, media, healthcare.

FAQ

Questions buyers ask us

AI can draft a strategy in minutes. Why would we pay for one?

You shouldn't pay for the document. AI will give you a plausible strategy, and a similar one to every competitor that asks. You pay for what it can't supply: evidence from your own buyers and data, judgment from operators who have run these P&Ls, and the buy-in to act. We use AI for the research legwork, so your fee goes to decisions and results, not slides.

What does StatsLateral do?

We help leadership teams at growth-stage and PE-backed companies make better product, go-to-market and AI decisions, and build them into the business. We design the strategy, build the capability with your team, run it until it performs, then hand it over.

What kinds of problems do you take on?

Product strategy (portfolio, platform, pricing and packaging), go-to-market strategy and systems (positioning, sales architecture, CRM, martech and salestech), and AI and data (readiness, data foundations, AI cost, agentic workflows, and team AI with teamctx). Most engagements touch more than one.

How does an engagement start?

With Design & Prove. We select one consequential problem, establish a baseline, and validate the approach on real work before you commit to a larger build.

What do we own at the end?

Everything needed to run and improve the capability: playbooks, systems and workflows, integrations, decision history, SOPs and operating metrics, plus any AI agents and evaluation methods we built. Ongoing support from us is optional.

How are engagements priced?

Fixed scope and milestone-billed against named deliverables. No hourly billing and no open-ended retainers. We scope on the first call; a statement of work typically follows within 5 business days.

What is teamctx, and do we have to buy it?

teamctx is our open-source (MIT) context layer. It keeps a team's current decisions, assumptions and owners in Git, available to every AI tool the team uses. There's no licence to buy. We use it in team AI engagements so the context stays in your repository after we leave.

Who do you work with?

Leadership teams at Series A–C and PE-backed companies, typically $10M–$300M in revenue, in the US and EU.

How is StatsLateral different from McKinsey, Bain, or BCG?

Senior operators only. Fixed scope with no hourly billing. We build and run a working capability rather than hand over recommendations, and we design every engagement so you stop needing us.

Bring one problem that matters.

A product bet, a stalled pipeline, a team whose AI isn't paying back. In 30 minutes we'll tell you how we'd approach it and what it would take.

Book a 30-minute conversation
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