NYMLOTH

The AI-native
operating layer

Accelerating high-intensity knowledge work with agentic systems.

MERT GULLEROGLU · FOUNDER 8 JULY 2026
01 — BACKGROUND 02 / 12

Built by an investor, for investment firms.

BACKGROUND
  • Employee #1 of a public equity fund grown from scratch to $11B: ~20%+ annual returns over 8 years, $3B overseen at peak
  • Led a research team in software and semiconductors
  • Delivered production-ready agentic systems to investment and advisory firms
  • Continuous test users at QIA, Ashburton, Lombard Odier, Federated Hermes
PAST MANDATES
  • Event-driven fund, US Midwest
  • Sustainability fund, Australia
LIVE MANDATES
  • M&A advisory, Istanbul (next slides)
  • Dutch Climate Transition PE

ONE OPERATING LAYER FOR AI-NATIVE KNOWLEDGE WORK: PE · VC · M&A ADVISORY · PUBLIC MARKETS

NYMLOTH
02 — THE AI-NATIVE FIRM 03 / 12

The scale ceiling is shattering for knowledge work.

Headcount and coordination capped growth and quality. With agents, the caps are gone and market shares will follow.

TODAY — FRAGMENTED
THE AI-NATIVE ERA
7% — THE LEADER
3%
2.5%
2%
1.5%
…PLUS HUNDREDS MORE AT 1–3%
15% — UNREACHABLE WITH HUMAN THROUGHPUT
25% — THE SAME FIRM, AI-NATIVE
20%
18%
2%
1.5%
…ONLY TENS REMAIN IN THE TAIL. THE REST ABSORBED OR EXITED

10× SPEED · 10× APERTURE · ~100% ROBUSTNESS VS 50–60% IN HUMAN ORGS

Examples: Block targets $2M gross profit per employee (4× pre-COVID). Kirkland & Ellis invests $500M into its own platform. Starbucks builds AI software to replace Microsoft and IBM tools. Sierra’s internal agent, Pinecone, writes 70% of its pull requests. Similar systems run at Shopify, Box, Deel and Browserbase.

NYMLOTH
03 — STATE OF THE INDUSTRY 04 / 12

Better eyes and ears are deployed. Nothing moved.

95%
Of enterprise GenAI pilots deliver no measurable P&L impact
MIT · 2025
56%
Of CEOs report no significant financial benefit from AI
PWC · 4,700 CEOS
42%
Of AI projects now abandoned, up from 17% in one year
S&P GLOBAL

Brilliant AI tools bolted onto the same way of working. The work still leaks at every handover, humans remain the integration layer, and the org moves at human copy-paste speed.

BCG: AI value is 70% operating model, 10% tools. Most invest in the 10%. McKinsey: high performers are 2.8× more likely to have fundamentally redesigned workflows (55% vs 20%).

NYMLOTH
04 — NYMLOTH SPINE 05 / 12

Eyes and ears can't coordinate. A spine can.

TOOLS CHANGE. MODELS CHANGE. THE SPINE STAYS.

Every tool and model is a socket on the spine. Tuck in the best one today, tuck it out tomorrow. No vendor lock, no re-platforming. One place to easily maintain and extend.

MILLIMETRICALLY YOURS

Spine encodes your workflows, domain knowledge, standards, edge cases, judgment, in a way that evolves in time with every process cycle.

37% of enterprises now run 5+ models in production (a16z, 2025). OpenAI fell from ~50% of enterprise share to ~25%, Anthropic now #1 at ~32% (Menlo). One CIO: "all the prompts have been tuned for OpenAI". Re-tuning is engineering time you pay at every switch.

NYMLOTH
05 — WHAT THE SPINE DOES 06 / 12

AI you own. AI you command.

Memory is your prime property. Every decision and artefact stored in full context, as time series.

Audit and improve every stage. Agentic runtimes are traceable, explainable and editable.

One edit updates the whole firm. A new screening rule, risk limit or valuation method applies immediately.

Every process run is a learning cycle that compounds. Two-weekly process, 1% better each cycle: +30% in a year. 5%: +250%.

Sentinels scan the world 24/7. Filings, deals, news, emails, calendars: processes are triggered just in time.

Govern the process instead of doing the job. Every run observable step by step, every instruction editable in minutes.

NYMLOTH
06 — THE SPINE 07 / 12

Work flows down the spine. Learning flows back up.

EVERY RUN IMPROVES THE NEXT — CYCLE TIME ↓ · QUALITY ↑
Trigger
Scheduled, manual, events like filings, deal signals
Agents
Research, draft, model, qualify
Review / Decide
Evaluate end-results
Iterate
Human–agent collaboration
Deliver
Finished work, in your everyday tools + data systems
MODELS
Claude · Gemini · GPT-x
TOOLS & DATA
market data · registries · docs · crm
YOUR SYSTEMS
Google Workspace · Microsoft Office · mail · chat
SOCKETS — TUCK IN, TUCK OUT
ARTIFACTS
memos · profiles · models · shortlists
MEMORY
what worked, what failed per run
DOCTRINE
your know-how, standards, encoded
STORES — EVERYTHING STAYS YOURS
AGENTS  ·  HUMAN JUDGMENT GATE
NYMLOTH
07 — CASE: M&A DEAL SOURCING 08 / 12

Complete sub-sector sweep, under one hour.

110
Companies discovered and deep-profiled
FROM 10 DISCOVERY STRATEGIES
48
Memo-grade prospects, every claim sourced
31 STRONG-FIT WITH INVESTMENT MEMOS
220
Buyers mapped and matched by name
165 SPONSORS + 55 STRATEGICS
10 DISCOVERY STRATEGIES, RUN IN PARALLEL

Industry associations and their boards, targeted M&A news, trade fairs, buyer-record adjacencies, recognition lists, industrial-zone tenants, foreign chambers, enterprise-software adoption.

11 WEDGES, EVIDENCE-SCORED

Generational transition, sponsor exit pressure, carve-outs, growth, customer quality and concentration, regulatory tailwinds and headwinds, distress, innovation, cross-border arbitrage.

NYMLOTH
08 — (CASE CONT’D) WHAT THE PARTNER SEES 09 / 12

Finished work, not tools.

THE MEMO
Generated investment memorandum in Google Docs

Delivered per qualified prospect: thesis, why-now signals, named buyers.

THE PIPELINE
Live deal funnel in Google Sheets

The universe lives in your Sheets and your CRM, synchronized for convenience.

NYMLOTH
09 — (CASE CONT’D) THE BLUEPRINT 10 / 12

A whole firm as an instrumented graph.

A LIVE MANDATE MAP — >50% OF PROCESS + DOCUMENTS AUTOMATED
DEAL FUNNEL
MANDATE PHASE 1
NOTES
Origination: build from taxonomy + monitoring deals
Prospects database
Company profiles
Intro meeting
Scoring & Qualification
Send proposal & track
Buyers database
Mandate agreement
Get documents from company
Financial model
Information memo
Q&A with company. Multiple rounds.
Teaser · potential buyers’ list
Market research
TARGET: 50/50 AI–HUMAN
AGENT-RUN
HUMAN
SHARED
  Autonomously (i) build / update the seller database from the sub-sector taxonomy, (ii) build / update the buyer database, (iii) monitor relevant deals and deliver a curated report, (iv) pre-meeting company briefs.
  Orchestrate the pursuit: automatically build the client’s folder and chat channel, send the intro email and ask for a meeting.
  Post-score: if worth pursuing, send the customized proposal.
NYMLOTH
10 — NYMLOTH APPROACH 11 / 12

Three stages, measurable outcomes.

01 — DISCOVER

Map the workings

We create a full-fidelity map of your workflows, systems, data and institutional knowledge to design your agentic spine, targeting:

  Same output, fewer people

  More from the same team, in quality and output

  Doing things you couldn’t before

02 — BUILD

Live in 30 days

Within thirty days your first system runs in production, doing real work, not sitting in a pilot. That's faster than onboarding a new hire. We measure the impact against the baseline we mapped, hand the controls, and tune it on live outcomes until it earns your trust.

03 — EXPAND

AI-Native in 6 Months

Weekly check-ins. Test and improve the first system. Strategize a roadmap to expand the spine with new workflows until your core operations run entirely on agentic systems. Your team operates at a new altitude, and the business scales far beyond what headcount alone allows.

NYMLOTH

Alpha is your job.
We handle the rest.

MERT GULLEROGLU · MERT@NYMLOTH.COM +31 6 1960 3995