Akil Ventures helps enterprises and nonprofits make fragmented records usable by people and AI agents through consulting, education, and implementation of products we've already built.
Whether the data is NYC's public records, a nonprofit's grants ledger, or an enterprise's CRM, AI systems need the same things: stable identifiers, source context, plain-English meaning, and a way to know what still needs human verification.
Agencies build for transparency. Portal vendors build for publishing. AI companies build for general reasoning. The layer that makes records usable in real workflows is usually missing.
askAkil.ai is the guided workbench for people. Akil MCP brings the same source-backed civic records into AI clients and agent workflows. Same record layer, different entry points.
Intelligence Layer
Raw public data can tell you what appears in a row. Akil's intelligence layer helps explain what that row means, how it connects to other records, and what it still cannot prove.
Agency portals, open-data feeds, spatial layers, state records, federal records, and source documents.
Source-aware schemas, entity anchors, address-to-parcel joins, interpretation notes, coverage windows, and workflow logic.
Tools, reports, MCP access, diligence packets, district briefings, business checks, and reusable cited answers.
Building class, permit status, violation status, license status, contract amount, payment amount, ownership text, and public-meeting records are interpreted in their source context.
People, organizations, vendors, licensees, applicants, owners, lobbyists, committees, addresses, BBLs, BINs, and source record IDs remain distinct until stable anchors justify a match.
Outputs disclose the applied search window, Akil mirror coverage, source freshness, and the possibility that older or outside-scope records may exist.
Akil supports research and diligence, not final legal, tax, zoning, environmental, regulatory, or compliance determinations. The system keeps those limits visible.
Trust Checks
Akil does not just retrieve public records. It runs trust checks for the mistakes that matter: losing source attribution, hiding coverage limits, merging identities too quickly, overreading metrics, turning regulatory records into clearance, or masking degraded paths.
Checks that answers keep source names, filters, result caps, freshness notes, caveats, and verification paths visible.
Checks that windowed, capped, empty, or timed-out responses are not treated as full clearance or proof that a record does not exist.
Checks that names, owners, vendors, licensees, applicants, permits, payments, and certifications stay separate unless source anchors support a match.
Consulting & Education
AI systems need records that are structured, sourced, and understandable when they hit messy real-world data. We help enterprises and nonprofits build record and workflow layers grounded in their own data, their own teams, and their own accountability requirements. Advisory, training, hands-on build, or implementation of our existing products — scoped to the outcome.
Turn public records, internal databases, spreadsheets, PDFs, and APIs into structured tools that AI assistants can search, cite, and use reliably, including MCP servers, agent workflows, and the source context that keeps answers grounded.
Hands-on education for teams learning to work with AI agents, coding assistants, research tools, and MCP-connected workflows. We teach practical patterns for scoping tasks, verifying outputs, protecting sensitive data, and adapting as the tools change.
Nonprofit, healthcare, and public-sector systems: CRM cleanup, grant operations, compliance tracking, intake, finance workflows, and staff-facing tools. The goal is cleaner work and better decisions.
Products
Everything we build starts with a real workflow: finding the right public record, understanding a district, checking a property, tracing public money, or making nonprofit operations auditable. Clients can use these products directly, or we can implement variations for their domain.
askAkil.ai
The guided product experience for exploring NYC public records. Start with a map, address, building, district, organization, agency, license, or funding question and get source-backed answers with reusable identifiers, caveats, and suggested next checks.
Open the workbench →Akil MCP
The agent-facing layer behind Akil. Connect AI assistants and automations to structured NYC public records across funding, property, procurement, lobbying, land use, licensing, housing, and neighborhood context, with source context and caveats kept visible.
See MCP access →Akil OS
The same operating-systems discipline applied to nonprofit operations. Grants, finance, compliance, client management, and HR become modular records that connect through shared identifiers, permissions, and workflows.
Learn more →About
"Akil" means intelligent in Arabic — but not the artificial kind. The useful kind: knowing what question matters, which records matter, and what workflow should come next. Akil Ventures combines operator experience, public-sector data work, and AI-native product development to build systems that are legible, durable, and useful in the real world.
Jie brings over 20 years of experience spanning proprietary trading, scaled operations, and technology consulting — with a foundation in information systems and business technology from Carnegie Mellon University. He spent 11 years as a senior equity trader on Wall Street, then co-founded COFFEED, a social enterprise coffee company that grew to 16 locations, $9 million in revenue, and 120 employees. Today he works at the intersection of AI, operations, and public-sector data — building askAkil.ai, Akil MCP, and Akil OS.
We start by understanding how work actually happens: who enters data, who checks it, what breaks, what must be trusted, and what should be automated.
The AI field changes too quickly for stale playbooks. We teach from live practice: building systems, testing new tools, documenting what works, and knowing where agents still need human judgment.
Nonprofits, healthcare, community organizations, and public-sector teams need systems that handle messy data, privacy, compliance, and real accountability. That is the environment we build for.
One conversation. Clarity on what you need now — and what can wait.
or email us directly at [email protected]