# Serverlessvc.com: AI Software, Media & Investing Agency

> Serverlessvc.com is an AI-native agency delivering measurable business outcomes through Edge AI, Vertical AI, AI Agents, and LLM Frameworks. We operate across three practices: AI Software, AI Media, and AI Investing. Founded in 2024, headquartered in the United States, serving clients worldwide.

## Who We Are

Serverlessvc.com helps enterprises and founders move from AI experimentation to real-world impact. Our philosophy: outcomes first, systems over silos, human amplification, and calm precision.

- **AI Software Agency**: Edge AI, Vertical AI, AI Agents, LLM Frameworks
- **AI Media Agency**: Generative content, AI video production, distribution pipelines
- **AI Investing Agency**: Market signal analysis, portfolio intelligence, decision automation

## Core Pages

- [Home](https://serverlessvc.com/): Overview of all three agency practices and key outcomes
- [Solutions](https://serverlessvc.com/solutions.html): Deep-dive into AI Software, AI Media, and AI Investing offerings
- [Sepia: Private AI Browser](https://serverlessvc.com/sepia.html): Open-source secure AI browser engine; describe a goal, Sepia finds it, acts on it, scales it privately
- [Sepia Technical Whitepaper](https://serverlessvc.com/sepia-whitepaper.html): Architecture, security model, token economics, enterprise deployment, and ROI analysis for Sepia
- [Services](https://serverlessvc.com/services.html): Full catalog of client-facing services offered by Serverlessvc.com
- [About](https://serverlessvc.com/about.html): Mission, vision, and philosophy
- [Careers](https://serverlessvc.com/careers.html): Open roles and how to join
- [Culture](https://serverlessvc.com/culture.html): Company values and operating principles
- [Community](https://serverlessvc.com/community.html): Events, meetups, and AI community
- [Newsletters](https://serverlessvc.com/newsletters.html): AI insights and curated newsletters
- [Ebooks](https://serverlessvc.com/ebooks.html): Free AI ebooks and guides
- [Papers](https://serverlessvc.com/papers/): Chronological index of notable AI research papers with concise editorial summaries
- [Blog](https://serverlessvc.com/blogs/): Essays and market research on AI software, the AI data economy, AI-native film production, and building AI businesses
- [Contact](https://serverlessvc.com/contact.html): Get in touch

## Services

Full service catalog: https://serverlessvc.com/services.html

### Generative AI Native Solutions
End-to-end Generative AI product development for startups and enterprises:
- LLM fine-tuning, prompt engineering, and model selection
- Autonomous AI agents and multi-agent orchestration
- RAG systems, vector search, and knowledge bases
- AI copilots and embedded intelligence for SaaS products

### Recruiting & Staffing for Engineering Teams
Specialized talent acquisition for AI and software engineering roles:
- AI/ML engineers, data scientists, and researchers
- Backend, platform, and infrastructure engineers
- Engineering managers and technical leads
- Contract, fractional, and full-time placements

### Pre-seed Fund Raising & Pitch Deck
Fundraising strategy and execution for early-stage founders:
- Investor narrative and positioning strategy
- Pitch deck design and story architecture
- Financial model and funding round structuring
- Investor introductions and warm outreach

### Technology Architecture & GTM Strategy
System design and go-to-market strategy for AI-native products:
- AI system design and architecture reviews
- Cloud-native and serverless infrastructure planning
- ICP definition, pricing, and positioning
- GTM playbooks, sales motion, and channel strategy

### Data Labelling & Annotation for AI Labs
High-quality annotation services purpose-built for training and fine-tuning AI models:
- Text and NLP: intent classification, NER, sentiment, summarization
- Image and video: bounding boxes, segmentation, keypoints, OCR
- Audio and speech: transcription, speaker diarization, phoneme tagging
- RLHF and evaluation: human feedback, preference ranking, safety labelling

### AI Software Agency (Platform Practice)
Build production-grade AI systems at scale:
- **Edge AI**: deploy intelligence at the network edge for low-latency, privacy-preserving applications
- **Vertical AI**: domain-specific AI systems tailored to industry verticals (healthcare, finance, logistics)
- **AI Agents**: autonomous agents that plan, reason, and act across complex multi-step workflows
- **LLM Frameworks**: custom RAG pipelines, fine-tuning, prompt engineering, and LLM orchestration

### AI Media Agency
Scale content creation without quality compromise:
- **Generative Content**: AI-generated articles, social media, newsletters, and marketing copy
- **AI Video Production**: automated video creation, editing, and personalization at scale
- **Distribution Pipelines**: multi-channel automated content delivery and audience targeting

### AI Investing Agency
Amplify investment intelligence with AI:
- **Market Signal Analysis**: real-time monitoring of market trends, earnings, and macro signals
- **Portfolio Intelligence**: AI dashboards that surface risks and opportunities across portfolio companies
- **Decision Automation**: AI-assisted deal sourcing, due diligence, and investment memo generation

## Open Source Products

### Sepia: Private AI Browser Engine

Sepia is an open-source secure AI browser engine built for the agentic era. MIT License. GitHub: github.com/mohnishbasha/sepia

**What it solves:**
- Token bloat: Delivers an 80-token compact semantic view of any page instead of 8,700+ tokens of raw HTML
- Fragile selectors: Uses stable semantic handles (role + accessible name + ordinal) that survive DOM restructuring and site redesigns
- Bot detection: Validates JS/header browser profile coherence before every session

**How it works:** Plan → Observe → Act → Verify agent loop. Serializer and resolver are pure functions with no LLM calls. Only the agent module has side effects.

**Interfaces:**
- CLI: one-shot `sepia run "goal"` returning typed RunTrace JSON
- HTTP server: REST API with bearer-token auth, configurable concurrency, Kubernetes Helm chart
- MCP stdio: 18 browser tools (observe, click, type, scroll, tabs, etc.) for Claude Code, Claude Desktop, and Codex

**Privacy & security:** Credentials are redacted before every model observation. Ephemeral browser profiles by default. Model output never eval'd, typed action enum only. Confidence threshold (default 0.7) refuses to act on ambiguous elements.

**Model compatibility:** Any OpenAI-compatible endpoint: Anthropic Claude, OpenAI GPT-4o, OpenRouter, or local Ollama (no API key needed for local inference).

Product page: https://serverlessvc.com/sepia.html
Technical whitepaper: https://serverlessvc.com/sepia-whitepaper.html
GitHub repository: https://github.com/mohnishbasha/sepia

## Key Outcomes

- Media campaign scale with AI-generated and distributed content
- Workflow automation via autonomous AI agents reducing manual effort
- Investment signal speed through continuous AI-powered market monitoring

## Newsletters

- **Snack on AI** ([snackonai.com](https://www.snackonai.com)): Free weekly AI newsletter. Bite-sized insights for builders, founders, and AI-curious readers.

## Papers

A chronological index of notable AI research papers with concise editorial summaries. Focus areas: AI safety, alignment, agents, LLMs, and applied AI research.

Index: https://serverlessvc.com/papers/

### Featured Summaries

- **Automated Researchers Can Reliably Mitigate Alignment Failures** (August 2026): Anthropic. Authors: Chen Yueh-Han, Jiaxin Wen, Jan Hendrik Kirchner. Claude Opus 4.8 agents ("Automated Alignment Researchers" / AARs) reliably discover post-training methods that mitigate ten alignment failures (deception, sycophancy, jailbreaks, prompt injection, hallucination, social bias, privacy violation, reward hacking, power seeking, concealing uncertainty) while preserving general capability. Methods generalize to held-out benchmarks, multi-turn Petri audits, and models up to 4.7× larger than the target model, and outperform ideas from 28 experienced human researchers within ~6 hours of search at $4/hour vs $150/hour. Summary: https://serverlessvc.com/papers/automated-alignment-researchers-2026-08.html · arXiv (HTML): https://arxiv.org/html/2608.28945v1 · arXiv (PDF): https://arxiv.org/pdf/2608.28945v1

## Blog

Essays and market research from the Serverlessvc.com team on AI software, the AI data economy, RL environments, AI-native media production, agents, and building AI businesses.

Index: https://serverlessvc.com/blogs/

### Posts

- **The Compound Startup Sandwich** (September 2026): Author: Mohinish Shaikh. An analysis of what the compound startup becomes in the AI era: build the data foundation below SaaS and the agents above it, and the product surface in the middle stops being a moat. Supply side: Epoch AI measures GPT-4 level capability falling from $37.50 to $0.12 per million tokens between March 2023 and December 2024 (312x in 21 months), and GPT-3 level from $60.00 to $0.18 (333x); AI-authored code share now runs from 26.9% to about 75% depending on method; Rox reports building a sequencer in 6 months and enrichment and a dialer in 3 months each for roughly $20M over 2.5 years. Foundation side: 60% to 80% of enterprise AI project effort is data preparation, B2B contact data decays about 2.1% a month (22.5% a year), Gartner puts poor data quality at about $12.9M per organisation per year and expects 60% of AI projects without AI-ready data to be abandoned through 2026. Demand side: sellers spend about 40% of their time selling, unchanged in five years. Incumbent case study from Salesforce FY26 audited results: $41.5B revenue up 10%, five service lines renamed to Agentforce with no change in revenue allocation, Q4 constant-currency growth of 37% (including $388M of acquired Informatica revenue), 8%, 7%, 3% and -1%, Agentforce ARR $800M (1.9% of FY26 revenue, about 13% of the $5.99B R&D line), and Data 360 ingesting 112 trillion records of which 53 trillion (47%) arrived via Zero Copy, up 310%. Buyer context from Zylo's 2026 index: 305 apps, $55.7M average annual SaaS spend, $19.8M of unused licences. Includes a seven-question self-test for locating your own layer and a counter-case covering the 79% adopt versus 11% in production gap, Gartner's expectation that over 40% of agentic AI projects are cancelled by 2027, token COGS and distribution. Read: https://serverlessvc.com/blogs/the-compound-startup-sandwich.html

- **Alpha Without Prediction** (September 2026): Author: Pragadeesh VS. A review of the 2026 evidence on language-model agents in markets, drawn from six parallel research investigations. Core finding: agents do not raise skill per bet, they raise how many independent bets you can make, so the value is breadth (the square-root-N term in Grinold and Kahn's fundamental law) rather than forecasting. Reality check: with a trial ledger and deflated Sharpe, no agent-discovered strategy passed certification (design Sharpe 1.69, deflated 0.86 over 102 trials, 0.18 out of sample), a planted future-peeking strategy with Sharpe above 34 passed deflation with a perfect score (multiple-testing correction does not catch leakage), nine of ten agents had negative stock-selection alpha under masked-ticker factor attribution, and subtracting memorised knowledge cut in-sample returns 45% on average. Production evidence: two 2026 fleets (~3,500 vaults, then ~550 perpetual-futures agents) produced 7.5M model calls and negative $217,000 realised PnL, 15% of agents net positive against 53% of retail, portfolios converged (1,544 of 3,454 vaults bought the same token within an hour), and 41-54% of observations recorded fabricated funding income. Three frontier models spanned 263.27-264.37 bp of regret with overlapping intervals at a 25x cost spread; behaviour lives in the operating layer (risk slider, candidate list, order path), not the prompt, and a mechanical stop-and-target bracket earned 39 bp per position. Eleven signal families graded: durable (analyst report prose, 1.19M reports, 68 bp alpha t=2.64, IR 1.23, and sentiment earns nothing; the overnight earnings-transcript window, IC 0.11, Sharpe 2.28; uncertainty and evasion for volatility, 43.8% of out-of-sample variance, sign-free; 8-K sub-item reclassification, 292,984 filings, precision 12% to 96%; decomposed disagreement), decaying (estimate revision momentum, disclosure language change), unproven (LLM-built supply-chain graphs where extraction and alpha literatures never overlap; XBRL statement analysis, whose bridging paper was retracted), illusory (insider and congressional disclosure; fraud prediction, AUC 0.96 random split versus 0.68 company-isolated). Options: the volatility risk premium is still wide (5.41 points in 2026, positive on 95.4% of days) but option alpha has been zero since a May 2012 structural break, so you are paid beta; premium has migrated into index correlation structure, oil and gold, while single-name earnings vol inverted (realised-to-implied 85% to 104%). Also covers a six-test evaluation checklist, deployment patterns at Balyasny, Bridgewater, Man Group, Avala Global and D.E. Shaw, the case for small local models over frontier models for classification, and seven experiments nobody has run. Not investment advice. Read: https://serverlessvc.com/blogs/alpha-without-prediction.html

- **What If a Movie No Longer Needed to Cost Millions?** (September 2026) - Serverless Ventures, Media. A line-by-line cost model of AI-native film production. Baseline: a representative $10M feature (production unit 37%, cast 15%, VFX 13%, contingency 14%). Empirical control: Hanuman Ansh, made for ~Rs 2 crore ($227k) and grossing Rs 72.32 crore ($8.2M) by day 27, a ~36x gross return, produced by 21-year-old debut producer Anupriya Nagar. Finding: feature budget shape is close to scale-invariant, so the production model, not the price level, is what AI changes. Four tiers of restructuring: tools-in-old-workflow $8.03M (19.7% cut), restructured workflow $3.86M (61.4%), no star premium $1.79M (82.1%), and AI-native with collapsed creative leadership and fully virtual environments $1.18M (88.2%), including an explicit $120k inference bill for ~144,000 delivered frames. Shoot days fall 42 to 4; the saving is in days, not day rates. Architecture: a consistency control plane (character identity embeddings, wardrobe continuity, location geometry, prop registry, LUT chain) that every generator reads from and writes back to, making this a state management problem rather than a model quality problem. Second-order effects: theatrical breakeven falls from ~$25M to ~$2.65M, a $10M fund finances 9 films instead of 1, and the binding constraint migrates from production to discovery. Thesis: the real disruption is that a film stops being an artifact and becomes a build, compiled from a source repository with a dependency graph. Read: https://serverlessvc.com/blogs/what-if-a-movie-no-longer-needed-to-cost-millions.html

- **Build the Environments, Not the Workforce** (September 2026): Authors: Mohinish Shaikh, Pragadeesh VS. A market-entry assessment of six high-value AI data categories for a two-person, engineering-led startup with an India-based workforce. Recommendation: reinforcement-learning environments with working verifiers: the only category where the deliverable is software, the buyer pays per artifact rather than per hour, and engineering is the moat. Covers price anchors (UI gym ~$20k, complex product replica ~$300k, quarterly contracts $300k-$500k, exclusivity 4-5x), incumbent mapping (Mechanize, Halluminate, Prime Intellect, HUD; Scale, Surge, Mercor, Handshake), margin structure, certification gates (SOC 2 Type II, ISO 27001, ISO 42001), DPDP Act and data-residency constraints, worker-classification risk, and a twelve-month three-stage entry plan. Read: https://serverlessvc.com/blogs/build-the-environments-not-the-workforce.html

## Careers

Open roles include:
- AI Researcher Intern (internship; Austin, TX or remote; AI Research)
- AI Platform Engineer (full-time; remote within the USA; Engineering)

See all roles: https://serverlessvc.com/careers.html

## Contact

- Website: https://serverlessvc.com
- Contact form: https://serverlessvc.com/contact.html

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RSS feed for blog posts and paper summaries: https://serverlessvc.com/feed.xml

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