LangChain LangChain

LangChain

AI Destination

Dataddo is the complete business data layer for LangChain - turnkey. It doesn't just connect LangChain to your business data; it delivers curated metadata, sensitivity classification, and security guardrails so every answer stays grounded, governed, and safe. No pipelines to build.

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DATA TO AI

From your business systems to any AI, governed end to end

Business systems

CRM, marketing, advertising, ERP, finance, support, databases, files

CRM & sales
Salesforce Dynamics 365 Pipedrive
Marketing
HubSpot Mailchimp Klaviyo
Advertising
Google Ads Meta Ads LinkedIn Ads TikTok Ads
ERP & finance
SAP Oracle NetSuite Xero
Databases & warehouses
PostgreSQL MySQL Snowflake BigQuery Databricks Redshift
Files & spreadsheets
Google Sheets Amazon S3 CSV / SFTP
400+ connectors
Extract
Dataddo Dataddo
SmartCache query-ready store

Extracted data is landed, deduplicated and kept fresh - so agents query a stable store instead of hammering live business systems.

Built-in guardrails
PII hashing & masking
Sensitive fields are hashed at ingest - the model never sees raw identifiers
Data quality firewall
Schema, freshness and anomaly checks block bad records before they reach the cache
Access policies
Row and column level permissions decide what each agent may retrieve
Full audit trail
Every model query is logged - who asked what, and what was returned
Business context via metadata
Table & column descriptionsBusiness glossaryMetrics & definitionsRelationshipsLineage & freshness

The model learns what a table means, not just what columns it has.

MCP
LLMs & agents

Connect over MCP - no custom pipeline per model

Claude
Gemini
OpenAI
Mistral
Perplexity
Grok
What the model can do
  • Answer business questions from governed, current data
  • Explore metrics without a hand-built pipeline per model
  • Stay inside policy - nothing ungoverned is reachable
Governed data in · trusted answers out
WITH VS. WITHOUT

The same data, a very different result

Point LangChain at the same CRM data - deals, tickets, contacts, and companies:

Without Dataddo With Dataddo Outcome for you
Business context & relations The model sees raw tables and field names. It has to guess what each field means and how deals, tickets, contacts, and companies relate - often getting the joins wrong. Every field ships with a plain-language definition and its relations across deals, tickets, contacts, and companies, so the model knows the schema before it reads a single row. Answers grounded in your real business
Freshness & quality signals No way to tell whether a record is current or reliable. Stale or incomplete data is treated the same as fresh, trustworthy data. Each field carries freshness timestamps and quality metrics, so the model can weight or flag data instead of trusting everything equally. Decisions on data you can trust
Token consumption High. The model burns tokens exploring the schema, sampling rows, and retrying until it understands the data. 50-90% lower. The context is supplied up front, so the model skips the exploration and goes straight to the answer. 50-90% less token spend
Processing time Slow. Most of the run is spent on discovery, data wrangling, and disambiguation before any real analysis begins. Much faster. With the groundwork already done, the model spends its time answering, not exploring. Answers in seconds, not minutes
Model tier & cost Needs a frontier model to reason through raw, unlabeled data - the most expensive option per query. Smaller, cheaper models handle the same questions, because the hard reasoning about structure is already solved. Money saved on cheaper models
Answer quality Prone to wrong joins, hallucinated fields, and ungrounded numbers that are hard to catch. Grounded, consistent answers tied to defined fields and real relations. Harder to measure, but the difference shows. Answers you can actually rely on
HOW IT WORKS

Everything between your data and LangChain is already built

1

Connect a source

Choose from 400+ connectors - databases, warehouses, and SaaS apps - and authorize in a few clicks.

2

Dataddo prepares the data

Automatic quality checks, PII controls, and business metadata are applied on the way through.

3

LangChain retrieves on demand

Your assistant queries governed, ready-to-use data over the open MCP standard - with no warehouse in between.

CAPABILITIES

Built for feeding AI, not just moving rows

No infrastructure

No warehouse or data lake to provision or pay for - Dataddo takes care of it, with 400+ ready-made connectors available out of the box.

Guardrails built in

Data Quality Firewall in blocking mode, PII exclusion, and column hashing (md5 / xxh3) before data ever reaches the model.

Business metadata

Dataset and field descriptions give the AI semantic grounding, with sensitivity flags on the fields that need them.

Historical data

Time-aware retrieval through configurable write strategies, so the AI can reason over change, not just the latest snapshot.

Freshness you can trust

Extraction timestamps and stable natural keys make it clear how current each answer is.

Works with your AI

LangChain and other clients connect over the open MCP standard - no proprietary lock-in.

SECURITY & GOVERNANCE

Your data stays yours

Permission model

Control exactly which datasets and fields each client can reach.

Blocking-mode quality rules

Records that fail your rules are stopped before they reach the model.

Deterministic hashing

Hash identifiers with md5 or xxh3 so data can be joined without ever being exposed.

USE CASES

What your team can ask on day one

Use case What you can ask Typical connectors
Marketing performance Ask what you spent and what it returned across every ad platform - no dashboard to open first.
Google Ads Meta Ads LinkedIn Ads GA4 HubSpot + 400 more
Revenue & pipeline Surface at-risk deals, forecast changes and pipeline movement from live CRM and billing data.
Salesforce HubSpot Pipedrive Stripe + 400 more
Support & product copilots Ground an assistant in current tickets and operational data, so answers reflect what is happening now.
Zendesk Intercom Jira PostgreSQL + 400 more
Analytics in plain language Let anyone query governed warehouse data in plain language, with permissions enforced by Dataddo.
Snowflake BigQuery Databricks Redshift + 400 more
Finance & operations Answer finance and ops questions spanning ERP and accounting systems from one place.
SAP Oracle NetSuite Xero QuickBooks + 400 more
FAQ

Frequently asked questions

Do I need a warehouse to use LangChain with my data?

No. Dataddo serves data to LangChain directly from SmartCache, so you can start without provisioning a warehouse or lake. If you later need one, the same platform delivers to BigQuery, Snowflake, and Databricks.

What is MCP?

MCP (Model Context Protocol) is an open standard for connecting AI clients to external data and tools. LangChain uses it to retrieve governed data from Dataddo on demand.

Can I control what LangChain can access?

Yes, completely. You define exactly which datasets and fields are exposed, and that definition is deterministic and under 100% your control. LangChain can only reach what you have explicitly published - nothing else is reachable.

Where is my data hosted? Can I choose the region?

You can. Dataddo runs across 64 global hosting locations, so you can keep data in the region your policies require. For the most security-aware data, Dataddo can also be deployed on-premise, so the data never leaves your own environment.

Is my data encrypted?

Yes - we encrypt everything, in transit and at rest, across the whole pipeline.

Is data access logged?

Yes. Every query and data access is logged, giving you a full audit trail of who asked what and what was returned.

Is my data used to train models?

Dataddo is a data pipeline, not a model provider - it moves your data, it does not train on it. Whether LangChain retains or trains on the data you send is governed by your agreement with its provider, so review their terms for specifics.

Which sources are supported?

400+ sources, including databases, cloud warehouses, and hundreds of SaaS APIs. If something you need is missing, you can request it.