Navigating a sea of paperwork, scattered throughout varied platforms, generally is a daunting activity, usually resulting in sluggish decision-making and missed insights. As organizational information and knowledge multiplies, groups that may’t centralize or floor the precise info rapidly will wrestle to make selections, innovate, and keep aggressive.
This weblog explores how the brand new Discuss to My Docs (TTMDocs) agent gives an answer to the steep prices of information fragmentation.
The excessive price of information fragmentation
Data fragmentation is not only an inconvenience — it’s a hidden price to productiveness, actively robbing your workforce of time and perception.
- A survey by Starmind throughout 1,000+ information employees discovered that workers solely faucet into 38% of their out there information/experience as a result of of this fragmentation.
- One other research by McKinsey & Associates discovered that information employees spend over 1 / 4 of their time trying to find the data they want throughout totally different platforms corresponding to Google Drive, Field, or native programs.
The constraints of current options
Whereas there are just a few choices in the marketplace designed to ease the method of querying throughout key paperwork and supplies residing in a wide range of locations, many have important constraints in what they’ll truly ship.
For instance:
- Vendor lock-in can severely hinder the promised expertise. Except you might be strictly utilizing the supported integrations of your vendor of selection, which in most situations is unrealistic, you find yourself with a restricted subset of data repositories you’ll be able to hook up with and work together with.
- Safety and compliance concerns add one other layer of complexity. In case you have entry to 1 platform or paperwork, you might not want entry to a different, and any misstep or missed vulnerability can open up your group to potential threat.
Discuss to My Docs takes a special method
DataRobot’s new Discuss to My Docs agent represents a special method. We offer the developer instruments and assist it’s essential to construct AI options that really work in enterprise contexts. Not as a vendor-controlled service, however as a customizable open-source template you’ll be able to tailor to your wants.
The differentiation isn’t delicate. With TTMDocs you get:
- Enterprise safety and compliance inbuilt from day one
- Multi-source connectivity as an alternative of vendor lock-in
- Zero-trust entry management (Respects Present Permissions)
- Full observability by DataRobot platform integration
- Multi-agent structure that scales with complexity
- Full code entry and customizability as an alternative of black field APIs
- Trendy infrastructure-as-code for repeatable deployments
What makes Discuss to My Docs totally different
Discuss To My Docs is an open-source software template that provides you the intuitive, acquainted chat-style expertise that fashionable information employees have come to count on, coupled with the management and customizability you really want.
This isn’t a SaaS product you subscribe to; however moderately a developer-friendly template you’ll be able to deploy, modify, and make your personal.
Multi-source integration and actual safety
TTMDocs connects to Google Drive, Field, and your native filesystems out of the field, with Sharepoint and JIRA integrations coming quickly.
- Protect current controls: We offer out-of-the-box OAuth integration to deal with authentication securely by current credentials. You’re not making a parallel permission construction to handle—should you don’t have permission to see a doc in Google Drive, you gained’t see it in TTMDocs both.
- Meet knowledge the place it lives: In contrast to vendor-locked options, you’re not compelled emigrate your doc ecosystem. You possibly can seamlessly leverage information saved in structured and unstructured connectors like Google Drive, Field, Confluence, Sharepoint out there on the DataRobot platform or add your information regionally.
Multi-agent structure that scales
TTMDocs makes use of CrewAI for multi-agent orchestration, so you’ll be able to have specialised brokers dealing with totally different facets of a question.
- Modular & versatile: The modular structure means you can even swap in your most popular agentic framework, whether or not that’s LangGraph, LlamaIndex, or every other, if it higher fits your wants.
- Customizable: Wish to change how brokers interpret queries? Regulate the prompts. Want customized instruments for domain-specific duties? Add them. Have compliance necessities? Construct these guardrails immediately into the code.
- Scalable: As your doc assortment grows and use instances turn out to be extra advanced, you’ll be able to add brokers with specialised instruments and prompts moderately than making an attempt to make one agent do every thing. For instance, one agent would possibly retrieve monetary paperwork, one other deal with technical specs, and a 3rd synthesize cross-functional insights.
Enterprise platform integration
One other key facet of Discuss to my Docs is that it integrates along with your current DataRobot infrastructure.
- Guarded RAG & LLM entry: The template features a Guarded RAG LLM Mannequin for managed doc retrieval and LLM Gateway integration for entry to 80+ open and closed-source LLMs.
- Full observability: Each question is logged. Each retrieval is tracked. Each error is captured. This implies you might have full tracing and observability by the DataRobot platform, permitting you to really troubleshoot when one thing goes unsuitable.
Trendy, modular parts
The template is organized into clear, unbiased items that may be developed and deployed individually or as a part of the complete stack:
| Element | Description |
| agent_retrieval_agent | Multi-agent orchestration utilizing CrewAI. Core agent logic and question routing. |
|
core |
Shared Python logic, frequent utilities, and capabilities. |
| frontend_web | React and Vite internet frontend for the consumer interface. |
| internet | FastAPI backend. Manages API endpoints, authentication, and communication. |
| infra | Pulumi infrastructure-as-code for provisioning cloud assets. |
The ability of specialization: Discuss to My Docs use instances
The sample is productionized specialised brokers, working collectively throughout your current doc sources, with safety and observability inbuilt.
Listed here are just a few examples of how that is utilized within the enterprise:
- M&A due diligence: Cross-reference monetary statements (Field), authorized contracts (Google Drive), and technical documentation (native information). The permission construction ensures solely the deal workforce sees delicate supplies.
- Scientific trial documentation: Confirm trial protocols align with regulatory tips throughout a whole lot of paperwork, flagging inconsistencies earlier than submission.
- Authorized discovery: Search throughout years of emails, contracts, and memos scattered throughout platforms, figuring out related and privileged supplies whereas respecting strict entry controls.
- Product launch readiness: Confirm advertising and marketing supplies, regulatory approvals, and provide chain documentation are aligned throughout areas and backed by certifications.
- Insurance coverage claims investigation: Pull coverage paperwork, adjuster notes, and third-party assessments to cross-reference protection phrases and flag potential fraud indicators.
- Analysis grant compliance: Cross-reference finances paperwork, buy orders, and grant agreements to flag potential compliance points earlier than audits.
Use case: Scientific trial documentation
The problem
A biotech firm making ready an FDA submission is drowning in documentation unfold throughout a number of programs: FDA steering in Google Drive, trial protocols in SharePoint, lab experiences in Field, and high quality procedures regionally. The core drawback is making certain consistency throughout all paperwork (protocols, security, high quality) earlier than a submission or inspection, which calls for a fast, unified view.
How TTMDocs helps
The corporate deploys a personalized healthcare regulatory agent, a unified system that may reply advanced compliance questions throughout all doc sources.
Regulatory agent:
Identifies relevant FDA submission necessities for the precise drug candidate.
Scientific evaluate agent:
Critiques trial protocols in opposition to trade requirements for affected person security and analysis ethics.
Security compliance agent:
Checks that security monitoring and adversarial occasion reporting procedures meet FDA timelines.
The consequence
A regulatory workforce member asks: “What do we want for our submission, and are our security monitoring procedures as much as normal?”
As a substitute of spending days gathering paperwork and cross-referencing necessities, they get a structured response inside minutes. The system identifies their submission pathway, flags three high-priority gaps of their security procedures, notes two points with their high quality documentation, and gives a prioritized motion plan with particular timelines.
The place to look: The code that makes it occur
One of the best ways to know TTMDocs is to take a look at the precise code. The repository is totally open supply and out there on Github.
Listed here are the important thing locations to start out exploring:
- Agent structure (agent_retrieval_agent/custom_model/agent.py): See how CrewAI coordinates totally different brokers, how prompts are structured, and the place you’ll be able to inject customized habits.
- Instrument integration (agent_retrieval_agent/custom_model/instrument.py): Exhibits how brokers work together with exterior programs. That is the place you’d add customized instruments for querying an inside API or processing domain-specific file codecs.
- OAuth and safety (internet/app/auth/oauth.py): See precisely how authentication works with Google Drive and Field and the way your consumer permissions are preserved all through the system.
- Internet backend (internet/app/): The FastAPI software that ties every thing collectively. You’ll see how the frontend communicates with brokers, and the way conversations are managed.
The way forward for enterprise AI is open
Enterprise AI is at an inflection level. The hole between what end-user AI instruments can do and what enterprises really want is rising. Your organization is realizing that “adequate” client AI merchandise create extra issues than they clear up while you can not compromise on enterprise necessities like safety, compliance, and integration.
The longer term isn’t about selecting between comfort and management. It’s about having each. Discuss to my Docs places each the facility and the pliability into your arms, delivering outcomes you’ll be able to belief.
The code is yours. The probabilities are countless.
Expertise the distinction. Begin constructing right now.
With DataRobot software templates, you’re by no means locked into inflexible black-box programs. Achieve a versatile basis that allows you to adapt, experiment, and innovate in your phrases. Whether or not refining current workflows or creating new AI-powered purposes, DataRobot offers you the readability and confidence to maneuver ahead.
Begin exploring what’s potential with a free 14-day trial.
