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Abstract An $$n \times n$$ matrix with $$\pm 1$$ entries that acts on $${\mathbb {R}}^{n}$$ as a scaled isometry is called Hadamard. Such matrices exist in some, but not all dimensions. Combining number-theoretic and probabilistic tools, we construct matrices with $$\pm 1$$ entries that act as approximate scaled isometries in $${\mathbb {R}}^{n}$$ for all $$n \in {\mathbb {N}}$$. More precisely, the matrices we construct have condition numbers bounded by a constant independent of $$n$$. Using this construction, we establish a phase transition for the probability that a random frame contains a Riesz basis. Namely, we show that a random frame in $${\mathbb {R}}^{n}$$ formed by $$N$$ vectors with independent identically distributed coordinate having a nondegenerate symmetric distribution contains many Riesz bases with high probability provided that $$N \ge \exp (Cn)$$. On the other hand, we prove that if the entries are sub-Gaussian, then a random frame fails to contain a Riesz basis with probability close to $$1$$ whenever $$N \le \exp (cn)$$, where $c<C$ are constants depending on the distribution of the entries.