With particular because of Arkaprabho Ghosh and David Reed.
As AI continues to rework the enterprise panorama, the problem for giant organizations isn’t simply adopting the expertise—it’s scaling it successfully. At Cisco, we acknowledged that whereas our groups have been keen to construct Retrieval-Augmented Technology (RAG) purposes, the method was usually fragmented. Builders have been spending months stitching collectively completely different elements of a RAG pipeline—comparable to loaders, splitters, embedding fashions, and vector databases. Every element carried its personal studying curve and operational overhead. The burden of evaluating an amazing variety of open-source instruments and endlessly experimenting with varied configurations to search out the fitting match for particular use circumstances finally led to inconsistent requirements, technical debt, and widespread “expertise 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 fulfill enterprise-standard workloads.
Simplifying the AI Journey
DRIFT was constructed with a easy premise: software groups ought to give attention to constructing AI-first experiences and enterprise logic, not on the heavy lifting of infrastructure. We’re eradicating the limitations to entry by offering a platform that handles the complexity of information pipeline orchestration, permitting groups to fast-track their AI journey with out the necessity for intensive 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 consumer in search of an intuitive interface, DRIFT supplies a real end-to-end growth and experimentation setting.
The Cisco-on-Cisco Benefit: Constructed for Scale & Safety
DRIFT is a robust 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 massive volumes of enterprise information 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 offers DRIFT the high-performance compute spine wanted for demanding AI workloads comparable to inferencing, embeddings, and reranking. By operating on-premise throughout a number of Cisco Knowledge Facilities, DRIFT combines scale, robust safety, excessive availability, and operational management in a approach 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 via a sturdy, modular pipeline structure:
- Doc Preprocessing: We assist numerous doc sources and codecs, standardizing numerous enterprise information right into a constant, model-ready format. We even leverage Imaginative and prescient Language Fashions (VLM) to transform photographs inside paperwork into textual content representations.
- Clever Splitting and Hybrid Processing: DRIFT helps a wide range of splitting algorithms, together with the flexibility to protect a doc’s structural formatting throughout the splitting course of. For paperwork with combined content material, it additionally allows a hybrid strategy that selectively processes photographs—serving as a extremely efficient price optimization approach.
- Embedding and Ingestion: Groups can select from a set of normal embedding fashions or convey their very own. We provide seamless integration with each shared multi-tenant in addition to devoted Vector databases to swimsuit a wide range of enterprise use circumstances. Our platform helps each key phrase and semantic search algorithms, making certain environment friendly ingestion and retrieval that meet enterprise SLAs.
- Retrieval and Reranking: DRIFT permits for configurable hybrid search and metadata filtering, making certain that retrieved information is exact. Our reranking capabilities additional refine outcomes based mostly on relevance, considerably rising accuracy.
- Adaptive Structure: Designed for the long run, DRIFT helps evolving use circumstances, together with Agentic RAG and Graph RAG, making certain enterprise purposes can scale as AI architectures advance.
- Constructed-in Testing and Analysis: Builders can take a look at retrievers towards pattern queries and work together with LLMs immediately inside the platform to validate generative summaries earlier than deployment.
Why is DRIFT a Sport-Changer:
- API-First Structure: DRIFT was constructed from the bottom up with an API-first strategy. 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 present enterprise purposes and workflows.
- Full Transparency and Experimentation: We’ve got moved away from the “black-box” strategy 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 elements of their pipelines, permitting them to fine-tune, take a look at, and optimize for max accuracy.
- Curated, Accountable AI: We remove the guesswork of evaluating open-source libraries. DRIFT supplies fashions which might be already vetted and accredited by Cisco’s Accountable AI (RAI) and governance groups.
- Diminished Know-how Fatigue: By offering a curated suite of industry-standard elements, we save groups from “evaluation paralysis.” We deal with the mixing to allow them to give attention to 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—comparable 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. Throughout the first 12 months, we’ve seen vital adoption with over 600 builders having constructed greater than 1,500 pipelines throughout numerous enterprise models, together with Finance, Provide Chain, Engineering, Authorized, IT Operations, and Folks and Communities.
By decreasing the time required to construct a knowledge pipeline from months to minutes, DRIFT has develop into a important engine for Cisco’s AI technique, enabling groups to experiment quickly and ship high-accuracy, AI-first options at scale.
Trying Forward
The success of DRIFT is a testomony to the collaborative spirit at Cisco. By working throughout groups—from IT & Operations to our varied enterprise models—we’ve created a instrument that not solely powers inside AI assistants (like our company-wide HR assistant) but additionally supplies a basis for future product integrations.
As we proceed to iterate, DRIFT stays dedicated to serving to Cisco groups transfer sooner, experiment extra, and ship the subsequent era of AI-powered options to our workers, prospects and companions.
