We use it ourselves first, then bring it to others.
From data collection to reports, course materials and review, Tako's internal technical staff all work through the same AI-logic work system.
The same system can also support large enterprises with LLM adoption and application development.
I'm screening environments that suit solo operators, such as Cursor or Slack; but token costs would be high, so that question is parked for now.
The AI already knows what it needs to know; next is mastering Tools().
Completed workDelivery Record
Counted by completed deliverables: deck pages, course-material language versions, per-pool estimates and independent acceptance checks.
LLMs & Local Deployment
Repo list
Enterprise LLMs
Adoption and application development, extending the same work foundation.
Local Deployment
Local first; the cloud fills in on hard problems.
Four Languages · Multi-market · Well-connected
Chinese · English · Vietnamese · Spanish: one set of course materials, developed across languages.
Cross-checking
Self-optimizing and logging lessons, continually reducing human error.
Four web images · illustrative · source licensing
- a close-up of a circuit board — Daniel Shapiro · Unsplash License: free for commercial and non-commercial use, no permission from or attribution to the photographer required; selling photos without significant modification, or compiling photos to build a competing image service, is prohibited.
- Rows of black server racks with white logos in a data center — imgix · Unsplash License: free for commercial and non-commercial use, no permission from or attribution to the photographer required; selling photos without significant modification, or compiling photos to build a competing image service, is prohibited.
- white and brown desk globe — Arpit Rastogi · Unsplash License: free for commercial and non-commercial use, no permission from or attribution to the photographer required; selling photos without significant modification, or compiling photos to build a competing image service, is prohibited.
- man programming using laptop — Danial Igdery · Unsplash License: free for commercial and non-commercial use, no permission from or attribution to the photographer required; selling photos without significant modification, or compiling photos to build a competing image service, is prohibited.
AI Adoption Consulting
Wiring business processes to AI: documents, reports, customer-service knowledge bases
Used internallyTechnical Consulting
Local model deployment, token usage control, review process design
Used internallyOn-chain Data Services
Pull data from public APIs and let AI turn it into reports; the charts on this page are the finished product
Used internallyAll three capabilities are already used in Tako's internal workflows. Services do not include investment advice.
Phone to Desktop AI
Hand off a task from the phone; the computer carries on the AI workflow.
Verifiable records first,
then usable judgment.
The blockchain packs transactions and state updates into blocks, linked by hashes. AI reads the data and finds patterns; on-chain actions are authorized by people.
- 01
Wallet Signing
The user confirms the transaction and authorizes the contract action.
- 02
Contract Execution
Updates assets and shares by programmed rules.
- 03
Block Confirmation
The transaction enters a block and is verified by the network.
- 04
API Data Pull
Reads records, pool and vault state.
- 05
AI Processing
Aligns timestamps, computes ranges and alerts.
- 06
Human Cross-check
Checks against the raw data, then decides strategy.
The two data types are pulled separately; exchange data is not treated as fully on-chain. How blocks work: Ethereum.org ↗
How a Neural Network Reads On-chain Data
On-chain records and market APIs are first shaped into features; the model then outputs range suggestions, alerts and the efficiency ratio. Data sources and timestamps must be aligned. (Architecture sketch, under construction)
What it learns
The past 8 months of volume distribution, price paths and pool depth; the label is the efficiency ratio computed after the fact
What it outputs
The price range for the next liquidity placement, an alert on whether to exit, and this week's estimated efficiency ratio
Who decides
The model only gives suggestions and a confidence level; adjusting the range, exiting or adding to a position is decided by people