Provably builds cryptographic proofs for data and for the systems that act on it, including databases, blockchains and AI agents. Its tools let a team show that a database answer is correct and complete, or that an agent’s claim about a tool call matches what the tool really returned, without asking anyone to trust the system that produced it.
It is built for data owners and for teams running multi-agent workflows in which one system’s output becomes another’s input. “Provably correct, not just probably right.”
At A Glance
| Vendor | Provably |
|---|---|
| Category | Verifiable data and runtime verification for AI agents |
| Deployment | Python SDK with CLI; hosted prover and verifier; fully local enterprise version |
| Agentic AI | SourceryKit runtime verification of agent tool calls; Switchboard agent to agent messaging |
| Market classification | AI Safety & Guardrails |
What Provably Does
When agents pass data to each other, or to people, the receiver usually has to take the answer on trust. Provably’s aim is verifiable data and runtime verification infrastructure so agents and humans can work together with accuracy, safety and integrity.
The starting point is the verifiable database. A data owner preprocesses its data once and can then serve SQL queries, each with a proof that the answer is correct and complete. The same idea then extends to agents: if every claim carries a proof, a receiver can check it instead of trusting it. The company’s research looks at integrity anchors across the agent lifecycle: tool use, handoffs, cross-agent protocols, learning and governance.
Products
Verifiable Databases
Verifiable Databases is for data owners whose query results need to be checked by whoever receives them. Every query result comes with a proof, produced by the QEDB protocol, which creates constant size proofs under 1 KB without using SNARKs. It connects to relational databases and supports aggregates (SUM, COUNT, MIN, MAX) and a wider set of general SQL, with joins, GROUP BY, LIKE and subqueries in development. An SQL IDE lets users browse data collections, write queries and receive verifiable analytics or raw data, depending on their permissions.
SourceryKit
SourceryKit is a runtime verification SDK for production agents. It is for teams whose agents call tools and then report the results onwards: each tool call is recorded in a QEDB table, the agent produces verifiable claims about tool outputs, and other agents or orchestrators check those claims while the workflow runs. A failed check can trigger a retry before the error spreads downstream, and logs are tagged with success or failure signals that complement existing observability tools. It covers tool calls to APIs, MCP servers, databases, RAG pipelines, internal tools and systems of record. In Provably’s own benchmarks across 15 AI models, SourceryKit detected a reported 100% of the covered deterministic errors. Guided recovery restored complete tool evidence in 53.3% of 60 failed runs, against 30.0% for a blind retry.
Switchboard
Switchboard provides secure agent to agent messaging, including with customers’ agents, so that messages crossing team or company boundaries can be trusted in the same way as tool results.
How It Works
| Component | What it does |
|---|---|
| Proofs | Agents and databases generate small proofs, about 1 KB each, that can travel across multi-hop workflows and team or network boundaries. |
| Verification without re-access | A downstream agent can check an answer without calling the source system again, which supports least privilege designs. |
| SDK and CLI | SourceryKit ships as a Python SDK with a CLI (pip install sourcerykit). It runs in the customer’s environment, and customers can host their own database so logs stay inside their infrastructure. |
| Prover and verifier | The verifiable database prover and verifier run on Provably’s side, and an enterprise version runs fully locally. |
| Data onboarding | Data owners onboard data, which is committed and preprocessed. Changed data is preprocessed again, with faster updates through APIs on request. |
Company Background
| Founders | Emanuele Ragnoli (CTO and founder), Alberto Trombetta (founder and scientific officer) and Simone Bottoni (founder) |
|---|---|
| Funding | CV VC wrote the first cheque |
| Research | The paper “qedb: Expressive and Modular Verifiable Databases (without SNARKs)”, by authors from Provably Technologies and Offchain Labs, is on the Cryptology ePrint Archive (2025/1408) and was accepted at ACM CCS 2026 |
Note: This overview is compiled from Provably’s publicly available information as of 4 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.