Head-to-head · updated 13 September 2026
DataShield vs Lightup: the table is healthy, but may the agent read it?
Lightup sells enterprise data observability. Their hero says it plainly: "Enterprise Data Observability at the Speed of Light." Point them at a warehouse. They learn what normal looks like. Then they page you when it stops. Three anomaly algorithms. Seasonality handling. No thresholds to hand-tune. Plus a one-click Recommendations feature that closes gaps for you. AMD, Skechers, and McDonald's run it. It's a good product. This page won't pretend otherwise.
We are not a data observability tool. DataShield has no monitors. No alerts. No freshness SLAs. No issue queue. We'll say that again further down, because it matters. What we do is govern the datasets an agent reads. We tokenize datasets at ingest. Agents query tokenized data over MCP. Turning a token back is a privileged, logged step. We check each tool call against the agent's current access. Then the call seals into a hash chain. You can check it yourself, no trust needed. Here's the honest split, rows Lightup wins included.
The short version
Pick DataShield when
- An agent is reading customer records. Someone will later ask you to prove the log wasn't edited. Our chain answers with math, not a PDF. Run the verifier.
- You need to pull an agent's access mid-session. The very next tool call should fail. Not the next token refresh. The next call.
- You want columns labelled as PII or PHI before anything touches them. Tokenized at ingest, not masked in a dashboard.
- The whole thing runs on your own infrastructure, on keys you hold. You want a price before you book a call.
Pick Lightup when
- Your problem is a pipeline that breaks quietly. Their models learn seasonality and trend from the past. You don't have to write the rules.
- You need alerts that reach a human. Slack, PagerDuty, Teams, email, with incidents and backtesting. We have none of that. Not this year.
- Your stack is Databricks, Snowflake, Dremio, or ksqlDB. You want quality checks in place this quarter. Their connector work is real.
- You want quality signals fed back into a catalog. They shipped a Collibra hookup in 2023. An Alation link followed.
Bottom line: Lightup tells you whether a table is trustworthy. DataShield decides whether an agent may read it. It keeps proof of the call. These are different jobs. Most teams who buy us already bought a tool like them.
Feature by feature
Competitor cells describe what Lightup's site and blog say. We use the date above. Did we get something wrong? Email support@myorg.ai. We'll fix it and credit you.
| What matters | DataShield | Lightup | Edge |
|---|---|---|---|
| Anomaly detection and monitoring | We have none. No statistical anomaly checks. No monitors on warehouse tables. Freshness SLAs aren't part of it. We profile and score datasets instead. That's not the same. We'd rather say so than fudge it. | The core of the product, and it's good. Three algorithms cover it. Values outside expectation. Sharp change. Slow-burn drift. Seasonality is baked in. Plus backtesting on history and feedback to tune accuracy. | ◇ |
| Incidents and alerting | Nothing to speak of. Guardian watches our own platform health. Not your pipelines. | Issues, Slack, PagerDuty, Teams, and email routing. Dashboards you can push into your BI tool. | ◇ |
| Profiling and quality scoring | Every dataset gets a full profile. Completeness, field stats, patterns, column semantics. Plus a relationship graph, quality metrics, lineage, and compliance flags. One trust score rolls up per entity type. Per domain, too, and across the estate. It breaks down by axis and updates hourly. | Metrics, sliced metrics, custom quality flags, and dashboards. Strong on the time series. Quieter on one deep profile of a single dataset. | ◈ |
| PII and PHI classification | 129 field classes. They cover PII, PHI, financial data, and secrets. That covers all 18 HIPAA Safe Harbor identifiers. Deterministic, no model in the loop. We stamp each verdict. So you can re-derive it and diff it later. | We found no classification or sensitive-data labels in their docs. Ask them what happens when a watched column holds a national ID. | ◆ |
| Tokenization and data handling | Deterministic, join-preserving, vault-reversible tokens, applied at ingest. Plus quasi-identifier generalization. Dates become year, decade, or age band. ZIPs become 3 or 4 digits. Phones, SSNs, and emails get partial masking. Each column gets a measured cardinality-reduction score. Catalog sample policy defaults to omit. The catalog never gets a copy of column values. | Not their vocabulary. They compute metrics over your data. Your warehouse handles sensitive values, whatever it already does. | ◆ |
| Audit evidence | SHA-256 hash chain, with Ed25519-signed checkpoints. We chain those checkpoints too. Verification names the exact failure: tampering, insertion, deletion, or truncation. Try it. | Langfuse tracing gives visibility into each AI session. Useful for debugging. We found no tamper-evidence method. | ◆ |
| Agent authorization | Each checked tool call passes a scope ceiling. Plus an access tier. Plus a pull-access re-check before dispatch. It fails closed. | Lightup Agentic authenticates with "your existing Lightup API token, so there is no separate authentication to manage." One token. The reach of your whole account. We found no per-call check. | ◆ |
| MCP and agents | More than 200 MCP tools, across Ontology, Auth, Corpus, and Lighthouse. Tool tokens carry scope ceilings. We meter each call. We attribute it to the agent. | Lightup Agentic is a real MCP server, in beta. It covers Claude Code, Claude Desktop, Gemini CLI, and other MCP clients. It drives their platform in plain language. Create metrics. Dig into issues. Onboard sources. | ◈ |
| Break-glass | Scoped, time-boxed emergency access for agents. It auto-revokes. It can't be quietly deleted from the log. | Not described in their public docs. | ◆ |
| GDPR erasure | Crypto-shred of per-subject key material. Plus ISO 27560 consent receipts. The audit chain still checks out afterwards. | A public DPA. Metric history runs 30 days or 6-plus months, by tier. They don't describe subject-level erasure. | ◆ |
| Deployment | Self-hosted, in your own cloud or data center. Or a dedicated single-tenant server we run. Ed25519 audit-signing keys sit on your instance, in a key directory you control. Rotation fails closed on an unknown key. KMS or HSM custody is a built seam in Auth. It's not a shipped integration yet. Tokenization keys sit in your setup, or come from your machine key today. Not in a KMS. | Cloud tier is cloud only. Enterprise adds "Cloud, Hybrid" on single-node or Kubernetes. They don't spell out what hybrid includes, publicly. | ◈ |
| Maturity signals | Live in production. Guardian and Lighthouse have run there since April 2026. SOC 2 isn't certified yet, and we say so. | Founded 2019. Roughly $9M disclosed Series A in 2023. CB Insights AI 100 in 2024. CIOReview award. Named enterprise logos. Longer track record than ours. A smaller balance sheet than their category rivals. | ◇ |
| Pricing | Our pricing. A scoped instant quote. No sales wall. | Two tiers, both behind a Get Quote button. No figures published at either level. | ◆ |
◆ DataShield leads◇ Lightup leads◈ comparable
Lightup claims come from lightup.ai and Lightup's own blog posts. Last checked 13 September 2026. We link them below, not from memory.
Three things you get here that you won't get from a data observability platform
Proof that survives an audit
A log that can be silently edited proves nothing. Ours is a hash chain, with signed checkpoints. The verifier tells you what broke. Not just that something did. EU AI Act Article 12 and HIPAA §164.312(b) reviewers ask about exactly this. Try it in your browser, no signup.
Authority that can change mid-flight
An analyst leaves on a Friday. Their agent is 20 minutes into a 40-minute job. DataShield re-checks the next tool call against current access. It fails closed. A watch layer sends an alert about it on Monday. How Auth does it.
The columns get labelled before the agent reads them
A quality score tells you a column is 98% full. It doesn't tell you it's full of national IDs. We sort against 129 field classes first. Then we tokenize. Then we let the agent query. What the catalog holds.
Where Lightup is genuinely stronger
Start with the thing we cannot do. Lightup learns what a metric normally does. It accounts for seasonality and trend. It flags the outlier, and no one writes a rule. You can backtest the rule against the past first. Then feed corrections back in. On top of that: issue tracking. Alert routing to Slack and PagerDuty. Reconciliation between two sources. Fix actions. Lineage for root-cause work. Since July 2025, quality checks on unstructured data too. Their Recommendations feature shipped in August 2025. It finds your coverage gaps and applies the fix in one click. That's six years of focused work. We have none of it.
The push-back is about what their agent story actually governs. Lightup Agentic is a genuine MCP server. The page is refreshingly concrete: Claude Code, Gemini CLI, SSE, or Streamable HTTP. But the credential is "your existing Lightup API token, so there is no separate authentication to manage." The record is Langfuse session tracing. That's a control plane for their product. An agent drives it with your whole account in its hands. It's not a data plane. Each read of a checked dataset there gets its own check. It's written into proof someone else can verify. If your agents only tune monitors, theirs is fine. If your agents read the records those monitors watch, that's our seam.
Questions worth asking both of us
These are the questions we'd want answered, if we were buying. Ask them on each call, ours too.
Can you cryptographically prove an audit log entry wasn't deleted?
DataShield: yes. Each record commits to the one before it. Checkpoints are signed and chained. Verification tells deletion apart from truncation and tampering. Run it against a sample chain at /verify. Lightup: their agentic page offers Langfuse tracing over AI sessions. That's visibility, not tamper proof. Ask them to show you a method.
What happens to a revoked agent mid-session?
DataShield re-checks access on each checked tool call. So a pull lands on the next call. Lightup Agentic runs on your own Lightup API token. We found no mid-session pull or scope ceiling in their docs. Ask how long a leaked token keeps working. And what it can reach while it does.
How does GDPR erasure interact with the audit trail?
DataShield crypto-shreds per-subject key material. It issues an ISO 27560 consent receipt too. Actor identities in the chain are HMAC-committed. So the proof still checks out once the subject is gone. Lightup publishes a DPA. It sets metric retention by tier: 30 days on Cloud, 6-plus months on Enterprise. Per-subject erasure is its own question. Ask for the method, not the retention setting.
Is DataShield a data observability tool? Do we drop Lightup?
No, and no. We have no anomaly checks. No monitors on your warehouse tables. No freshness SLAs. There's no issue queue either. A silent pipeline break is your pain? Buy a monitoring tool. Run us over the datasets agents read instead. There, the job is classification, authorization, and proof. Plenty of teams sensibly run both. Lightup's own Collibra and Alation work shows this. They expect to sit next to other tools.
Lightup ships an MCP server too. What's different?
Theirs drives their platform. Create a metric. Dig into an issue. Onboard a source. All in plain language. Nice work, and we'd use it. Ours is where the checked data itself gets queried. The tool token carries a scope ceiling. The call gets checked before dispatch. It seals into a chain. One controls a product. One controls access to records. Ask both of us which one your agent is holding.
Does DataShield have SOC 2?
Not yet. We won't fake it. Auth is live. It has a public threat model, and a verifier anyone can run. Guardian and Lighthouse have run in production since April 2026. Design-partner terms include source escrow. A small vendor isn't a single point of failure, that way. Details on the security page. Lightup publishes no badge we could find either. So ask us both.
- Lightup's positioning: "Enterprise Data Observability at the Speed of Light", "powered by AI anomaly detection and agentic interfaces." - lightup.ai, 13 Sep 2026
- Lightup Agentic is "a Model Context Protocol (MCP) server that connects your Lightup instance to AI coding assistants like Claude and Gemini". It's authenticated with "your existing Lightup API token". - lightup.ai, 13 Sep 2026
- Three anomaly algorithms (values outside expectations, sharp change, slow-burn trend change) with seasonality and backtesting on history. - lightup.ai, 13 Sep 2026
- Genie, a GenAI copilot assistant, launched in beta preview "Powered by OpenAI" with a bring-your-own-model option. - Lightup blog, 17 Dec 2024
- Lightup Recommendations: "intelligent suggestions for the next best action" that close data quality coverage gaps in one click. - Lightup blog, 27 Aug 2025
- Two tiers, Cloud and Enterprise, both gated behind Get Quote. Cloud is cloud-only with 30-day retention. Enterprise offers "Cloud, Hybrid" with 6+ months. - lightup.ai pricing, 13 Sep 2026
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AllEvery comparison
One honest scorecard per vendor.
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