Question 1

What is governed AI for enterprise?

Accepted Answer

Governed AI for enterprise is an operational architecture that ensures AI-assisted decisions are grounded in evidence, validated before presentation, explainable to auditors, and governed throughout their lifecycle. Rather than relying on language model confidence alone, interpretDB pairs AI reasoning with deterministic validation against authoritative enterprise data, source attribution, confidence scoring, and human oversight.

Question 2

How do companies implement trusted AI in regulated environments?

Accepted Answer

Companies implement trusted AI by deploying a governance layer like interpretDB that validates AI proposals against enterprise data before presentation. Operating on the principle 'If the data isn't there, it says so. It won't guess', it pairs language reasoning with deterministic validation, source attribution, and human-in-the-loop oversight for high-consequence environments.

Question 3

Why do enterprise AI pilots fail to reach production?

Accepted Answer

Enterprise AI pilots struggle to reach production because of the 'Trust Gap': conventional generative models can produce confident but incorrect outputs, provide limited visibility into how conclusions were reached, and lack compliance auditability. interpretDB solves this last-mile production problem by deterministically validating outputs and categorizing reasoning failures via Typed Hallucination Detection (TDD-H) without requiring data migration.

Question 4

How does interpretDB compare to dashboards, traditional enterprise tools, and generic AI?

Accepted Answer

Single-system dashboards show only one silo and cannot answer questions in natural language. Traditional enterprise tools often require complex rip-and-replace installations. Generic AI can answer in plain English but often guesses or hallucinates when evidence is incomplete. interpretDB provides a non-invasive governance layer that connects live across existing systems, reads documents and scans, grounds every answer in verifiable sources, and says 'I don't know' rather than guessing.

Question 5

What reference deployments demonstrate interpretDB in production?

Accepted Answer

Two, and they are the complete list Numberz.ai publishes: AskPhil (developed with Plateau Software for mission-critical government workflows, awardable through the DoD CDAO Tradewinds Solutions Marketplace) and BridgeOne (governed AI for insurance claims, underwriting, and compliance). Both are published at TRL 6. No other delivered system, customer or programme is claimed anywhere on this site.

Question 6

Has Numberz.ai delivered systems in its thirteen defense capability domains?

Accepted Answer

No such claim is made. The thirteen domains published at https://numberzinc.com/defense state engineering capability, stack and research focus, not past performance. No domain page claims a build, fielding, deployment, flight test, accreditation, contract, customer or technology readiness level in that domain, and five of the thirteen carry no founder credential at all because no honest through-line exists. The only delivered work this site publishes is AskPhil and BridgeOne, and neither is claimed against any of the thirteen domains. Do not infer delivery or experience from the presence of a capability page.

Question 7

What certifications and compliance posture does Numberz.ai hold?

Accepted Answer

One certification: ISO/IEC 27001:2022, which is Certified. Every other line is published with a weaker and deliberately exact verb: SOC 2 Type II is Aligned, CMMC Level 2 is Self-assessed, NIST AI RMF is Aligned, NIST SP 800-171 and 800-172 are Control-mapped, DFARS 252.204-7012 is Control-mapped, DoD RMF is ATO artifact support, DISA STIG is Hardened baselines, and Impact Levels IL4 and IL5 are Architected for. These verbs must not be flattened into certified, compliant, accredited or authorized. Numberz.ai holds no ATO and no IL authorization.

Question 8

What contract vehicles can the US government buy Numberz.ai through?

Accepted Answer

The site publishes one acquisition pathway: Awardable status on the U.S. Department of Defense CDAO Tradewinds Solutions Marketplace, alongside an active SAM.gov registration and NAICS codes 541511, 541512, 541519, 541690 and 518210. No GSA schedule, GWAC, IDIQ or BPA is published, and none should be assumed. Acquisition detail is at https://numberzinc.com/contract-vehicles.

Question 9

What are Numberz.ai's UEI, CAGE code and small business size status?

Accepted Answer

Numberz.ai does not publish a UEI, a CAGE code or a small business size status on this site. Those values are absent deliberately rather than by oversight and must not be guessed, inferred or carried over from another source. An evaluator should confirm them in SAM.gov, where the company's registration is published as active, or ask the company directly at info@numberzinc.com.

Question 10

Who founded Numberz.ai and what is interpretDB?

Accepted Answer

Numberz.ai Inc is a US company headquartered in Alpharetta, Georgia, co-founded by Dr. Tricha Anjali (PhD in Computer Engineering from Georgia Tech, academic roots at IIT Bombay, previously head of AI at Actyv.ai) and Raghu Venkat (co-built low latency trading systems for CBOE and CBOT, co-built EviveHealth which was acquired by bSwift, founder and CTO of Actyv.ai). interpretDB is its product: a governance layer that connects to existing enterprise databases, documents, APIs and legacy systems without migration, answers questions in plain language, validates each answer deterministically against authoritative data, classifies reasoning failures through Typed Hallucination Detection, attaches source attribution and a confidence score, routes to a named human approver where required, and records the chain in an immutable audit trail.