Companies · AI / ML
New York · NY, USA · AI / ML · founded 2025 · https://alterauth.com
Diligence memoA one-page analyst read on Alter — recommendation, valuation, rhythm, risks.→Alter: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Alter is one of 2067 AI / ML companies tracked from New York, NY, USA, on record since 2025. By capital raised it ranks mid-pack (ahead of 62% of sector peers), and mid-pack by modeled valuation est..
Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.
AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%
operates a technology-led product inferred from public copy
Grounded in: “You are a venture analyst”
Secure access control and authorization platform for agent workflows
Alter is a zero-trust identity and access control platform purpose-built for AI agents. It wraps every tool call in strong authentication, fine-grained authorization, and real-time guardrails, so agents can move fast without breaking things. Each request is verified at the parameter level, authorized against granular policies, executed with least-privilege access, and fully audited in real time. Unsafe actions, whether it’s a rogue DROP TABLE or a payment above policy limits, are blocked before they touch production. Behind the scenes, Alter manages credentials, issuing ephemeral, scope-narrowed access for every interaction, then rotating or expiring it in seconds. The result: no long-lived secrets, no blind spots, and no surprises in audit. With Alter, teams can move fast on AI agent initiatives while staying fully compliant with SOC 2, HIPAA, GDPR, and internal security standards. A CISO-ready dashboard delivers real-time visibility, detailed audit logs, and compliance-ready controls, removing silos, eliminating excessive permissions, and providing complete oversight of every agent workflow.
As reported in public records reported — not modeled.
Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.
No round amounts on record to chart.
No staged rounds to sequence.
Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.
Not enough modeled valuation points to chart a trajectory.
Benchmarked against 2067 companies in AI / ML. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.
Raised more than 62% of sector peers (real $). Modeled value above 62% of peers (estimate).
Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.
| Stage | Amount · real | Announced | Post-money · est | Value · est | Conf. |
|---|---|---|---|---|---|
| No rounds recorded. | |||||
Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.
Alter is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.
Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| Accord | AI / ML | — | — | — | same sector |
| Acely | AI / ML | — | — | — | same sector |
| Aedilic | AI / ML | — | — | — | same sector |
| Aemon | AI / ML | — | — | — | same sector |
| Affogato AI | AI / ML | — | — | — | same sector |
| Aftercare | AI / ML | — | — | — | same sector |
| Agentic Labs | AI / ML | — | — | — | same sector |
| Ai Aiba | AI / ML | — | — | — | same sector |
Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.
| Company | Sector | Stage | Value · est | Match |
|---|---|---|---|---|
| Escape Offensive security for the teams that are 100x outnumbered | AI / ML | — | — | 78% |
| Agency Agency replaces traditional security and compliance headcount with AI. | Professional Services | — | — | 76% |
| Multifactor Zero-trust authentication, authorization, and auditing for AI agents | Cybersecurity | — | — | 75% |
| Agentic Fabriq The control plane for AI agents. | Cybersecurity | — | — | 75% |
| Respan Self-driving observability, evals, and gateway for AI agents | AI / ML | — | — | 75% |
| Typewise Boosting customer service and sales productivity by 2-3x. | AI / ML | — | — | 75% |
| CodeStory Aide is an AI-native , privacy-first IDE built on top of VSCode | AI / ML | — | — | 74% |
| Intuned Code-first scrapers and RPAs — built and maintained by AI | AI / ML | — | — | 74% |
See where Alter sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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