maverickai-sea.com

How maverickai-sea was built.

Dealroom pressure test, primary. Models and agent, parallel tracks.

End-to-end. Solo. Singapore. 2026.

The Stack

TRAINING PRODUCTION RTX 3070 Ti 8GB VRAM Model 1 — 355M GPT-2 AWS g4dn T4 16GB VRAM Model 2 — 1.4B GPT-NeoX S3 Corpus Storage AWS EC2 t3.small ap-southeast-1 Nginx Deal Room maverickai-sea.com OpenClaw Agent Orchestrator Moltbook Agent maverickai-sea AWS SES [email protected] RentAHuman Human Intelligence

Two models. 355M complete. 1.4B planned next.

Model 1 — RAZER-355M

Parameters355M
ArchitectureGPT-2
HardwareRTX 3070 Ti
VRAM8GB
Corpus87GB
TokenizerGPT-2 BPE
StatusComplete
Training steps100,000 / 100,000
Final loss0.2952
HostedHuggingFace

Model 2 — 1.4B GPT-NeoX

Parameters1,414,600,000
ArchitectureGPT-NeoX
HardwareH100 80GB HBM3
Precisionbfloat16
Optimizer8-bit Adam
Batch Size8
Seq Length1024
Corpus57GB / 33 sources
TokenizerCustom BPE 32K vocab
StatusPlanned next phase — pending AWS vCPU quota (g4dn.12xlarge)

Training progress. 355M shipped. 1.4B planned next.

RAZER-355M finished at step 100,000 with final loss 0.2952. The 1.4B GPT-NeoX run is a planned next phase, pending AWS vCPU quota approval for g4dn.12xlarge.

lower is better ↓

What the models were trained on.

45%
20%
15%
10%
10%
General web (FineWeb, C4)
Financial & business news
Wikipedia
Academic papers
Operator reasoning patterns

22.7M records. 87GB raw.

The dealroom pressure test.

The primary product. A seller uploads their pitch material, the app assembles a simulated buying committee for the target customer, each exec raises objections against the material, and a gap report synthesises what the material is missing. Output is a results page, an optional rebuttal doc, and an optional read-only share link.

SYNC REQUEST ASYNC + ON-DEMAND Upload PDF, DOCX, or paste Industry + DM confirm inferred or user-provided Committee gen Claude Sonnet, per role Objection gen Sonnet, parallel per exec /confirm returns JSON Gap report streaming, cached Client polls /gap-report-status, 2s Rebuttal doc Markdown + PDF, on demand Share link 7-day token, revocable

Storage

Session history and share links are stored as JSON on disk under data/, with sensitive fields encrypted at rest using AES-256-GCM: customer name, deal size, material text, committee, objections, gap report, rebuttals. Writes are atomic — temp file plus rename — and serialised through a single-slot Promise queue so concurrent appends never tear. History entries expire 30 days after creation and are swept on an interval and lazily on load. Corrupt JSON files are preserved to a timestamped sidecar, never deleted.

Share links

Tokens are minted with crypto.randomBytes(32) and base64url-encoded. Each record stores only a SHA-256 hash of the owner's auth cookie, so revoke can be scoped to the original owner without keeping the raw cookie on disk. Links expire after 7 days. Expired or revoked tokens return 410 Gone with a no-store cache header. The public /shared/:token route is rate-limited to 60 requests per minute per IP, sets X-Robots-Tag: noindex, nofollow, and writes an access log with SHA-256-hashed IP and truncated user-agent. The log is capped at 10,000 rows and trimmed on each append.

Test discipline

Tests run with Jest against an in-process supertest harness. 451 tests across 15 suites cover route contracts, rate limiting, CSRF enforcement, the full share-link lifecycle (create, expire, revoke, rate-limit, rebuttal redaction), history encryption round-trip, and shared-view field parity. The sentinel convention — one unique string per rendered field, asserted to appear in the response body — was added in Phase 18 after a field-name mismatch shipped to prod where objection text rendered blank because the renderer read the wrong field names. Positive-content assertions now guard every surfaced field.

451
Tests passing
15
Jest suites
18
Phases shipped
30
Days history retained

How the Moltbook agent operates.

Every 30 min
Brain loop checks Moltbook for new activity
Every 4-8 hrs
Heartbeat generates and posts new content
Every 30 min
Engage timer browses submolts, upvotes, comments
Inbound comment
Auto-response generated within 30 min
RentAHuman bounty
Human attends enterprise AI event. Intel delivered to [email protected]

What's honest about this.

The 1.4B GPT-NeoX run is a planned next phase, pending AWS vCPU quota approval for g4dn.12xlarge. The 355M is complete and hosted on HuggingFace. Neither claims frontier-model performance. They exist to demonstrate end-to-end ownership of the training pipeline — corpus assembly, tokenizer training, distributed training, evaluation, and deployment.

The dealroom app does not use either of these local models. It uses Anthropic Claude Sonnet for committee generation, objection generation, and gap-report synthesis. The local models and the dealroom app are parallel demonstrations, not a single integrated system.

Right now.

...
Training Step
451
Tests Passing
...
Moltbook Karma
18
Dealroom Phases