Meraji Advisory
Advisory for PE/VC-backed software

Cut the cost structure. Fund the next revenue line.

I help operating partners and portfolio CTOs rebuild R&D and operations around AI, with a playbook already proven inside a high-growth tech scale-up.

Book an intro call See services
Track record

What the playbook did in one company

Across my tenure leading engineering, product and infrastructure for a 100+ person organization in North America, India and LATAM. Our applied AI work also won Best Paper at IEEE ICPRS 2025.

−91% Customer experience operating cost
before
after
End-to-end automation with AI document extraction, verification and fraud detection.
−83% R&D and FinOps spend
before
after
Spec-driven, AI-native SDLC with 3–4x feature velocity.
$100M New commercial revenue AI-first recommendation engines, B2B enterprise suites and direct-to-consumer funnels.
Services

Support at each point in the investment cycle

Pick the stage you're at. Every engagement starts with a scoped, fixed-fee piece of work, so you see results before committing to anything longer.

  1. Before close

    Technology & AI due diligence

    Architecture, team, cloud and LLM spend, and how defensible the AI really is. Findings come with costs attached, so they can go straight into the deal model.

    2–3 weeks · fixed fee
  2. First 100 days

    AI Cost & Velocity Diagnostic

    A cost baseline, an AI maturity score, the top five levers with dollar estimates and owners, and a 90-day plan the CTO can start on Monday.

    3 weeks · fixed fee
  3. During the hold

    AI-native transformation

    Hands-on with the CTO: an AI-native SDLC on one or two teams, FinOps and model routing, and agent workflows in operations, tracked against the value creation plan.

    90 days · ~1 day a week
  4. Before exit

    Exit readiness

    A technology and AI story a buyer's diligence team will believe: clean architecture documentation, cost metrics, and an evidence-backed AI roadmap.

    4–8 weeks

Fractional leadership

For portfolio companies with a leadership gap or a transformation that needs a senior owner.

Fractional CTO

Interim technology leadership through a search, a turnaround or a platform rebuild. Hands the seat over to a permanent hire.

Fractional Head of AI

Sets the AI strategy, picks the first use cases with real payback, and puts evals and cost controls in place before scaling.

Board technology advisor

A monthly session with the CEO and CTO, technology review ahead of board meetings, and support hiring senior engineering leaders.

For funds

Portfolio AI program. A working session for all your portfolio CTOs, followed by diagnostics at the three to five companies with the most to gain.

The playbook

Four moves that did most of the work

>80% of production code AI-generated

Spec-driven development

Engineers write precise specs; agents write and test the code. Review shifts from typing to judgment.

ticket → pull request

A context platform for agents

Repos, live APIs and technical docs fed to agents as one context, automating the SDLC from ticket creation to PR.

>50% lower LLM token cost

Model routing and FinOps

Each request goes to the cheapest model that can do it well, inside a cloud budget that is reviewed like any other P&L line.

zero production downtime

Monolith to multi-agent

Legacy services migrated to an event-driven, multi-agent architecture while the business kept running.

Contact

Start with a 30-minute call

Tell me about the portfolio company and the cost or velocity problem in front of you. I take on one or two engagements at a time.

LinkedIn: Sina Meraji, PhD