Company

We built what
the market needed
but didn't have.

Tether Connect exists because the organizations we spoke with kept describing the same problem: developers were using AI tools, security teams had no visibility, and the available solutions didn't fit.

Our Mission

Make AI use in enterprise engineering both safe and fast.

The assumption in most enterprise security is that you have to choose between developer productivity and organizational security. Block AI tools entirely, or accept that you can't see what's being shared. Neither is acceptable.

The deeper problem under that one: rules don't work on a generative surface. Regex DLP, allowlists, signature scanners — these were built for an enumerable world. Developers using AI don't paste literal "SECRET KEY = "; they paraphrase, refactor, brainstorm. There is no regex for "is this an exfil attempt?" So we built Tether to classify intent — what the developer is actually trying to do — and apply the policy response your security team chose for that intent.

Rules still matter. They're the deterministic floor — credential patterns, blocked destinations, hard compliance boundaries. The on-device judge sits on top, reasoning about everything regex can't. Compliant developers notice nothing. Non-compliant intent is caught before it causes harm.

The approach is endpoint-native because that's where the control has to live. A cloud proxy you can walk around isn't a control — it's a policy document with a certificate attached. We're not interested in building those. We're interested in building controls that actually work when an adversarial developer is trying to get around them.

We're a small, technical team. We're not trying to build a broad platform — we're trying to build the best solution to one specific, hard problem. That focus is intentional.

What we believe about
security products.

01

Honest About Scope

We're direct about what Tether does and doesn't cover. A clear threat model is more useful than marketing that implies total protection. We'd rather you understand the boundaries and trust what's inside them.

02

Controls That Actually Control

A security control that can be trivially bypassed isn't a control — it's liability. Every design decision we make is tested against an adversarial assumption. Can a motivated developer get around this? If yes, it's not done.

03

Developer Experience Matters

Security tools that create excessive friction get disabled, worked around, or abandoned. We design for the compliant developer first. When the experience is good for them, adoption succeeds and the controls hold.

04

Self-Hosted by Default

Your developers' code and AI interactions are sensitive. We don't think a cloud intermediary should touch that data. Self-hosted deployment is our default recommendation — not an afterthought for regulated industries.

05

Air-Gap Isn't a Niche

The assumption that "cloud is fine" excludes defense contractors, intelligence community work, and an increasing number of regulated industries with strict data residency requirements. We build for those environments too.

06

Pricing That Scales With You

Per-seat billing creates perverse incentives — it makes security more expensive as you hire. We believe enforcement cost should be infrastructure cost, not a tax on team growth. Our licensing model reflects that.

Why this problem
matters now.

92%
of developers use AI coding tools
Multiple industry surveys (GitHub, Stack Overflow, JetBrains) point to majority AI tool adoption among developers, with figures accelerating year over year. Exact numbers vary by methodology and role definition.
Few orgs
have technical AI egress controls in place
Most organizations have acceptable use policies. Very few have technical enforcement that actually intercepts and evaluates AI requests before transmission.
$4.88M
average cost of an enterprise data breach (IBM Cost of a Data Breach Report, 2024)
AI-assisted data exfiltration is an emerging vector that existing DLP and CASB tools weren't designed to address.

The combination of near-universal AI tool adoption and near-zero technical enforcement creates a window of exposure that is growing faster than enterprise security programs can respond to.

Regulatory frameworks are beginning to catch up. The EU AI Act, NIST AI RMF, and enterprise AI governance programs are creating documented requirements for controls over AI data handling. The organizations that have technical controls in place now will be ahead of compliance requirements as they crystallize.

We believe the endpoint is the right place to close this gap — not because it's easier, but because it's where enforcement needs to be for the controls to be meaningful.

Where we are.

2025

Founded

Tether Connect incorporated. Core enforcement architecture designed and initial development begun.

Q1–Q2 2026

Build Phase

Core enforcement pipeline in active development. Architecture validated across all five components.

H2 2026

Early Access

First deployments under evaluation agreements with design partners. Active development driven by real-environment feedback.

2027

General Availability

Production-ready release targeting Startup and Enterprise tiers. Compliance reporting features complete.

Interested in working with us?

Whether you're evaluating Tether for your org, exploring a partnership, or just want to understand the space better — we're happy to talk.