Accelerating Enterprise-Scale AI Growth & Experimentation
With particular due to Arkaprabho Ghosh and David Reed.
As AI continues to rework the enterprise panorama, the problem for big organizations isn’t simply adopting the know-how—it’s scaling it successfully. At Cisco, we acknowledged that whereas our groups have been keen to construct Retrieval-Augmented Era (RAG) functions, the method was typically fragmented. Builders have been spending months stitching collectively totally different parts of a RAG pipeline—akin to loaders, splitters, embedding fashions, and vector databases. Every element carried its personal studying curve and operational overhead. The burden of evaluating an awesome variety of open-source instruments and endlessly experimenting with numerous configurations to search out the proper match for particular use instances finally led to inconsistent requirements, technical debt, and widespread “know-how fatigue”.
To resolve this, Cisco IT created DRIFT (Doc Retrieval and Ingestion Framework Toolkit), a standardized, scalable platform that helps fast growth and experimentation in RAG workflows with the flexibility to scale to satisfy enterprise-standard workloads.
Simplifying the AI Journey
DRIFT was constructed with a easy premise: utility groups ought to concentrate on constructing AI-first experiences and enterprise logic, not on the heavy lifting of infrastructure. We’re eradicating the obstacles to entry by offering a platform that handles the complexity of knowledge pipeline orchestration, permitting groups to fast-track their AI journey with out the necessity for in depth ramp-up time on underlying, advanced applied sciences.
Whether or not you’re a hard-core developer requiring deep API-level management or a enterprise person searching for an intuitive interface, DRIFT gives a real end-to-end growth and experimentation atmosphere.
The Cisco-on-Cisco Benefit: Constructed for Scale & Safety
DRIFT is a strong instance of the Cisco-on-Cisco benefit—the place Cisco software program is constructed to run on Cisco’s personal AI infrastructure. Constructed on a cloud-native microservices structure and deployed on Kubernetes, DRIFT is engineered for agility, resilience, and enterprise-scale efficiency. Its asynchronous ingestion and file add structure is designed to deal with giant volumes of enterprise knowledge effectively, enabling high-throughput pipelines with out sacrificing reliability.
On the coronary heart of this basis are Cisco AI PODs powered by Cisco UCS-C885A {hardware}. This provides DRIFT the high-performance compute spine wanted for demanding AI workloads akin to inferencing, embeddings, and reranking. By operating on-premise throughout a number of Cisco Knowledge Facilities, DRIFT combines scale, sturdy safety, excessive availability, and operational management in a means that meets the wants of enterprise AI.
The result’s greater than only a trendy AI platform—it’s a clear demonstration of how Cisco AI software program and Cisco AI infrastructure come collectively to ship production-ready efficiency at scale. With DRIFT operating on Cisco AI PODs constructed on UCS-C885A, Cisco is showcasing an end-to-end AI stack that’s scalable, safe, and purpose-built for enterprise innovation.
The DRIFT Methodology: Powering Safe RAG
DRIFT streamlines the trail from uncooked doc to clever assistant by a sturdy, modular pipeline structure:
- Doc Preprocessing: We help various doc sources and codecs, standardizing various enterprise knowledge right into a constant, model-ready format. We even leverage Imaginative and prescient Language Fashions (VLM) to transform photos inside paperwork into textual content representations.
- Clever Splitting and Hybrid Processing: DRIFT helps quite a lot of splitting algorithms, together with the flexibility to protect a doc’s structural formatting in the course of the splitting course of. For paperwork with blended content material, it additionally allows a hybrid method that selectively processes photos—serving as a extremely efficient price optimization method.
- Embedding and Ingestion: Groups can select from a collection of ordinary embedding fashions or convey their very own. We provide seamless integration with each shared multi-tenant in addition to devoted Vector databases to swimsuit quite a lot of enterprise use instances. Our platform helps each key phrase and semantic search algorithms, guaranteeing environment friendly ingestion and retrieval that meet enterprise SLAs.
- Retrieval and Reranking: DRIFT permits for configurable hybrid search and metadata filtering, guaranteeing that retrieved knowledge is exact. Our reranking capabilities additional refine outcomes primarily based on relevance, considerably rising accuracy.
- Adaptive Structure: Designed for the long run, DRIFT helps evolving use instances, together with Agentic RAG and Graph RAG, guaranteeing enterprise functions can scale as AI architectures advance.
- Constructed-in Testing and Analysis: Builders can check retrievers towards pattern queries and work together with LLMs straight throughout the platform to validate generative summaries earlier than deployment.
Why is DRIFT a Recreation-Changer:
- API-First Structure: DRIFT was constructed from the bottom up with an API-first method. We offer complete, ready-to-use APIs for each step of the lifecycle—together with doc add, ingestion, retrieval, and configuration—enabling seamless integration into current enterprise functions and workflows.
- Full Transparency and Experimentation: We have now moved away from the “black-box” method to a real end-to-end growth and experimentation platform that empowers builders with full visibility. Groups have full management over configuration decisions for all parts of their pipelines, permitting them to fine-tune, check, and optimize for max accuracy.
- Curated, Accountable AI: We get rid of the guesswork of evaluating open-source libraries. DRIFT gives fashions which are already vetted and accepted by Cisco’s Accountable AI (RAI) and governance groups.
- Lowered Know-how Fatigue: By offering a curated suite of industry-standard parts, we save groups from “evaluation paralysis.” We deal with the combination to allow them to concentrate on innovation.
- Flexibility and Scalability: Whereas we offer normal, high-quality choices, DRIFT stays absolutely versatile. Groups can combine their very own customized Vector Databases or fine-tuned fashions—akin to these specialised for Cisco-specific monetary or technical terminology.
Driving Actual-World Affect
Since its MVP launch in January 2025, the adoption of DRIFT has been extraordinary. Inside the first 12 months, now we have seen important adoption with over 600 builders having constructed greater than 1,500 pipelines throughout various enterprise items, together with Finance, Provide Chain, Engineering, Authorized, IT Operations, and Folks and Communities.
By lowering the time required to construct a knowledge pipeline from months to minutes, DRIFT has turn out to be a essential engine for Cisco’s AI technique, enabling groups to experiment quickly and ship high-accuracy, AI-first options at scale.
Wanting Forward
The success of DRIFT is a testomony to the collaborative spirit at Cisco. By working throughout groups—from IT & Operations to our numerous enterprise items—now we have created a device that not solely powers inside AI assistants (like our company-wide HR assistant) but additionally gives a basis for future product integrations.
As we proceed to iterate, DRIFT stays dedicated to serving to Cisco groups transfer quicker, experiment extra, and ship the following technology of AI-powered options to our workers, clients and companions.
