Navigating a sea of paperwork, scattered throughout varied platforms, generally is a daunting process, usually resulting in gradual decision-making and missed insights. As organizational information and knowledge multiplies, groups that may’t centralize or floor the appropriate data rapidly will battle to make selections, innovate, and keep aggressive.
This weblog explores how the brand new Talk to My Docs (TTMDocs) agent gives an answer to the steep prices of data fragmentation.
The excessive value of data fragmentation
Data fragmentation isn’t just an inconvenience — it’s a hidden value to productiveness, actively robbing your workforce of time and perception.
- A survey by Starmind throughout 1,000+ information staff discovered that staff solely faucet into 38% of their accessible information/experience as a result of of this fragmentation.
- One other study by McKinsey & Associates found that information staff spend over 1 / 4 of their time trying to find the data they want throughout completely different platforms equivalent to Google Drive, Field, or native techniques.
The constraints of present options
Whereas there are a number of choices in the marketplace designed to ease the method of querying throughout key paperwork and supplies dwelling in a wide range of locations, many have important constraints in what they will really ship.
For instance:
- Vendor lock-in can severely hinder the promised expertise. Except you’re strictly utilizing the supported integrations of your vendor of selection, which in most situations is unrealistic, you find yourself with a restricted subset of knowledge repositories you’ll be able to hook up with and work together with.
- Safety and compliance issues add one other layer of complexity. If in case you have entry to at least one platform or paperwork, chances are you’ll 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 Talk to My Docs agent represents a special method. We offer the developer instruments and assist that you must 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 refined. 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 Current 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
- Fashionable infrastructure-as-code for repeatable deployments
What makes Discuss to My Docs completely different
Discuss To My Docs is an open-source utility template that provides you the intuitive, acquainted chat-style expertise that fashionable information staff have come to anticipate, coupled with the management and customizability you really need.
This isn’t a SaaS product you subscribe to; however reasonably a developer-friendly template you’ll be able to deploy, modify, and make your individual.
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 present controls: We offer out-of-the-box OAuth integration to deal with authentication securely by present credentials. You’re not making a parallel permission construction to handle—in case you don’t have permission to see a doc in Google Drive, you received’t see it in TTMDocs both.
- Meet knowledge the place it lives: In contrast to vendor-locked options, you’re not pressured emigrate your doc ecosystem. You’ll be able to seamlessly leverage information saved in structured and unstructured connectors like Google Drive, Field, Confluence, Sharepoint accessible 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 completely different elements of a question.
- Modular & versatile: The modular structure means you can too swap in your most well-liked agentic framework, whether or not that’s LangGraph, LlamaIndex, or some other, if it higher fits your wants.
- Customizable: Wish to change how brokers interpret queries? Alter the prompts. Want customized instruments for domain-specific duties? Add them. Have compliance necessities? Construct these guardrails straight into the code.
- Scalable: As your doc assortment grows and use instances change into extra advanced, you’ll be able to add brokers with specialised instruments and prompts reasonably than making an attempt to make one agent do the whole lot. For instance, one agent may 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 present 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’ve gotten full tracing and observability by the DataRobot platform, permitting you to truly troubleshoot when one thing goes unsuitable.
Fashionable, modular parts
The template is organized into clear, impartial items that may be developed and deployed individually or as a part of the total stack:
| Element | Description |
| agent_retrieval_agent | Multi-agent orchestration utilizing CrewAI. Core agent logic and question routing. |
|
core |
Shared Python logic, frequent utilities, and features. |
| frontend_web | React and Vite net frontend for the person interface. |
| net | 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 present doc sources, with safety and observability inbuilt.
Listed here are a number of 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.
- Medical 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 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 funds paperwork, buy orders, and grant agreements to flag potential compliance points earlier than audits.
Use case: Medical trial documentation
The problem
A biotech firm making ready an FDA submission is drowning in documentation unfold throughout a number of techniques: FDA steering in Google Drive, trial protocols in SharePoint, lab stories in Field, and high quality procedures regionally. The core drawback is guaranteeing 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.
Medical overview agent:
Evaluations trial protocols in opposition to business requirements for affected person security and analysis ethics.
Security compliance agent:
Checks that security monitoring and opposed occasion reporting procedures meet FDA timelines.
The end result
A regulatory workforce member asks: “What do we want for our submission, and are our security monitoring procedures as much as commonplace?”
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
The easiest way to grasp TTMDocs is to have a look at the precise code. The repository is totally open supply and accessible 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 completely different brokers, how prompts are structured, and the place you’ll be able to inject customized conduct.
- Instrument integration (agent_retrieval_agent/custom_model/device.py): Exhibits how brokers work together with exterior techniques. That is the place you’d add customized instruments for querying an inside API or processing domain-specific file codecs.
- OAuth and safety (net/app/auth/oauth.py): See precisely how authentication works with Google Drive and Field and the way your person permissions are preserved all through the system.
- Internet backend (net/app/): The FastAPI utility that ties the whole lot 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 need is rising. Your organization is realizing that “ok” shopper AI merchandise create extra issues than they resolve whenever you can not compromise on enterprise necessities like safety, compliance, and integration.
The long run isn’t about selecting between comfort and management. It’s about having each. Talk to my Docs places each the ability and the pliability into your palms, delivering outcomes you’ll be able to belief.
The code is yours. The probabilities are infinite.
Expertise the distinction. Begin constructing right this moment.
With DataRobot utility templates, you’re by no means locked into inflexible black-box techniques. Acquire a versatile basis that allows you to adapt, experiment, and innovate in your phrases. Whether or not refining present workflows or creating new AI-powered purposes, DataRobot offers you the readability and confidence to maneuver ahead.
Begin exploring what’s doable with a free 14-day trial.
