Poly Truth and Meme Punch stand out among below-$1 crypto picks alongside Sei in 2026 market watchlist.

A lot of coins sit well under $1, but only some have the setup to actually move toward it. The next crypto to hit $1 will probably come from a project that has more going for it than a low price tag.

This article looks at three picks worth a closer look right now. Poly Truth (PTRUE) and Meme Punch (MEPU) are still in presale, and Sei (SEI) is already listed and building momentum. Different stages, different stories, but all three are worth knowing.

Next crypto to hit $1: 3 Picks to watch

Three projects worth a closer look for those who are scanning for the next sub-$1 token with real upside.

1. Poly Truth (PTRUE)

Poly Truth is a prediction market intelligence tool. Not a trading platform, not a bot. The concept is that users receive AI-powered analysis that indicates which outcome the data actually supports and why, rather than speculating on prediction events.

The team constructed the platform’s three-part system around three characters. The Runners are AI bots that search the internet for information on current prediction events. The AI analyst known as the Starlet calculates probability scores, looks for patterns, and cross-references the sources. The Presenter delivers the final report in plain language.

A few things worth noting:

• 11.5 billion tokens are available, and it is based on Ethereum.
• Ten percent of the supply is reserved for staking rewards, and forty percent is allotted to the presale.
• Audited by Coinsult and SolidProof; both reports are available to the public.
• Team tokens have a 3-month cliff and a 12-month vest.
• ETH, BNB, SOL, USDT, USDC, card, and SEPA are among the available payment methods.

2. Meme Punch (MEPU)

The play-to-earn cryptocurrency game Meme Punch is based on a simple idea. Play and get real cryptocurrency after winning, as opposed to holding a memecoin and waiting for a pump. 

Five iconic meme-inspired characters — Pepe, Doge, Floki, Brett, and Pudgy Penguin — compete for supremacy in this medieval battle arena. Choose a knight, engage in PvP combat, move up the leaderboard, and receive in-game rewards in the form of MEPU. The token has actual use outside of speculation since it can be used within the game to access weapons, skins, and special abilities. 

Features worth knowing:

• Built on Ethereum, with a total supply of 10 billion MEPU.
• 40% of supply goes to the presale, with 14.5% for staking and 9.5% for in-game rewards.
• Marketing allocation sits at 16.5%, aimed at reaching gamers outside the crypto bubble.
• Payment options cover ETH, BNB, SOL, USDT, USDC, and card.

3. Sei (SEI) 

Sei is a high-speed Layer 1 blockchain built around fast trading, gaming, and other apps that need performance. After months of sideways action, it’s one of the better stories on exchanges right now.

The price action tells the recovery story clearly. SEI was sitting near $0.054 in mid-April, broke above the descending channel in early May, hit a peak of around $0.078 on May 10, and now trades near $0.067. That’s a 24% move off the April low, with the chart showing higher lows building.

A few catalysts are behind it:

• The Giga upgrade is rolling out through 2026, targeting over 200,000 transactions per second with sub-400ms finality.
• EVM migration is set to complete by June 15, 2026, opening the door to Ethereum developers and apps.
• Xiaomi partnership has SEI’s wallet preinstalled on devices outside China and the US, exposing the chain to a massive global user base.

Why these picks are worth watching

Each of the three picks holds its position for a different reason, but they all have one thing in common. Price alone won’t be enough for the next cryptocurrency to reach $1. It will require a strong reason for consumers to continue purchasing.

In order to provide prediction market traders with a real advantage, Poly Truth is developing an AI research tool. A memecoin can be transformed into a playable game with in-game features with Meme Punch. Real adoption is being pushed by Sei through the Giga upgrade, an EVM migration, and a partnership with Xiaomi.

The point is the combination of stages. The smaller entry and larger upside, should they land, are offered by the presales. SEI provides a project that is already demonstrating ecosystem progress and recovery. It’s important to be aware of the various bets and timelines.

Augustus Bank’s CEO, Ferdinand Dabitz, says legacy clearing banks cannot truly rebuild their cores for artificial intelligence and programmable money, as his startup moves closer to launching a US national bank designed around both.

The Office of the Comptroller of the Currency (OCC) granted conditional approval for Augustus Bank N.A. on Monday under the Guiding and Establishing National Innovation for US Stablecoins (GENIUS) Act, which created a federal framework for payment stablecoins and clarified how banks and certain nonbank entities can issue and integrate dollar-pegged tokens under federal oversight.

Augustus now plans to establish a full-service national bank in Dallas, Texas, focused on fully reserved stablecoins, AI-driven compliance and automation-heavy back-office processes. Dabitz told Cointelegraph it was just “a couple of months” from full approval and launch. However, final approval remains subject to pre-opening conditions.

The company is targeting the “broken” correspondent clearing business dominated by global banks such as Citi, arguing that incumbents cannot fully re-platform systems built for humans, not machines, that still close on weekends and rely on decades-old cores.

“The short answer is replacing them,” Dabitz said when asked whether Augustus could coexist alongside traditional clearing banks.

Augustus bets stablecoins and AI can remake clearing

Augustus began life in Berlin in 2021 as Ivy, a euro-clearing fintech that built a transaction banking platform for non-US financial institutions, fintechs and crypto firms.

Augustus received conditional OCC approval this week. Source: PR Newswire

The bank already runs euro payments and instant settlement for clients, including crypto exchange Kraken. “The clearing bank bond is truly broken,” he said, arguing there’s an opportunity to “rethink it as an application and deliver something pretty terrific.”

Related: JPMorgan to launch tokenized money market fund for stablecoin issuers

Central to Dabitz’s pitch is the belief that large banks can upgrade legacy infrastructure but cannot fundamentally rebuild around AI and tokenized money. “I’ve come to the conclusion it’s impossible to re-platform a bank,” he said.

Augustus plans a three-layer stablecoin model: using stablecoins as a funding rail for payments, as a treasury and liquidity tool to release what Dabitz estimates is around $3 trillion in trapped idle capital, and as the interface layer for AI agents interacting directly with money.

He said the model could enable real-time treasury optimization and allow AI systems to become “first-class customers” of the bank, handling tasks such as liquidity management and transaction monitoring on behalf of corporates.

Competition from banking giants

Dabitz’s argument comes as major banks accelerate their own AI and digital asset initiatives.

JPMorgan Chase says it invests more than $18 billion annually in technology, including AI, and Citi reported over $6.1 billion in clearing-related revenue in Q1 alone, highlighting the scale of the incumbent profit pool Augustus is targeting.

Dabitz argues his team can still move faster because it is designing AI and stablecoin workflows into its operating model from the outset rather than retrofitting existing systems.

Related: Argentine banks testing JPMorgan’s JPM Coin to speed up settlements: Report

He also described the US banking market as structurally under-innovated, noting that banking is unusually labor-heavy compared with other major industries, with people rather than assets forming a major part of operating costs.

Pushing AI deeper into banking operations

Augustus wants to compress processes such as transaction monitoring, case handling and suspicious activity reporting from “20 hours to 20 minutes” using AI, with humans supervising the systems rather than manually performing every step.

Critics question whether a young, AI-focused bank with a 25-year-old leader at its helm can safely automate compliance-heavy operations without introducing model risk, explainability problems or operational failures.

Dabitz said that only makes the challenge “more exciting” and that the company plans to work closely with regulators and banking executives to ensure “the checks and balances and the harness for the AI to operate in a safe and sound manner.”

Magazine: Bitcoin will not hit $1M by 2030, says veteran trader Peter Brandt

Gemini’s “agentic trading” lets AI models like ChatGPT and Claude plug into user accounts via MCP, executing crypto trades autonomously and turning AI from signal vendor into primary CEX client.

Gemini has rolled out “agentic trading,” a feature that lets AI systems like ChatGPT and Claude connect directly to user accounts and execute crypto trades autonomously on the exchange, rather than just spitting out trade ideas for humans to click. The move quietly shifts AI from being a glorified signal service to being a client class in its own right, with opaque, proprietary models now sourcing, routing, and managing a chunk of CEX order flow on their own.

According to Gemini’s own blog, “agentic trading means your AI agent acts on your behalf — placing trades, monitoring markets, and managing risk automatically,” with users defining strategies and constraints while the agent handles execution. Under the hood, Gemini has integrated its full trading API with the Model Context Protocol (MCP), an open standard originally built by Anthropic that lets AI agents call external tools and services; compatible models include Claude and ChatGPT, which can query markets, place orders and adjust positions over time. Third‑party write‑ups emphasize that Gemini is the first regulated US exchange to expose a dedicated “agentic” interface, turning centralized exchange infrastructure into a native venue for autonomous trading agents rather than just human click‑flow and traditional algos.

Gemini heats up the AI race

Practically, the system is built around modular “Trading Skills” — pre‑built functions AI agents can invoke to get real‑time market data, inspect order‑book depth and spreads, and pull historical candle data, with more complex order‑routing and risk modules promised over time. Users link their accounts to an AI model via MCP, set budget and risk limits, and then let the agent run strategies that can range from simple DCA or grid trading to multi‑leg structures and volatility plays, with Gemini stressing that “human oversight remains part of the design” through caps and rules. But the microstructure implication is obvious: once enough people plug in agents and walk away, a material share of resting and market orders on Gemini will be coming from black‑box models tuned to optimize for particular objectives, not from human decision cycles.

That changes who you are actually trading against. Historically, the story was “retail vs HFT vs a few prop‑shop algos”; now Gemini is effectively advertising “AI as a client type,” more akin to how prime brokers have algorithmic clients that are not directly human‑decisioned on each trade. In high‑volatility periods, tightly coupled agent strategies can amplify feedback loops — especially if many users are copying off the same “AI signals” or fine‑tuning similar models on overlapping data — and you can easily imagine clusters of agents front‑running naive human behavior or unintentionally engaging in coordinated patterns that look a lot like cartelized flow.

There is a clean contrast here with TON’s on‑chain “Agentic Wallets.” TON is pushing autonomy to the network edge: agents live in Telegram, manage non‑custodial wallets on TON, and interact with DeFi directly on an L1. Gemini is doing the opposite: recenters agentic trading inside a regulated, custodial CEX, where AI agents are tightly coupled to one exchange’s API and compliance perimeter. In both cases the future is the same: the next “HFT villain” in crypto will not be a named firm on the other side of your order, but a swarm of un‑audited models, systematically optimized around the fee, tax and KYC constraints their operators face — and increasingly treated by the infrastructure itself as the primary customer, with humans demoted to parameter‑setters and occasional override buttons.