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Solvd

by Solvd · Since 2011
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ActiveAvailable globallyCloud
Quick facts
VendorSolvd
Year launched2011
StatusActive
LocationUSA, Washington 1015 15th Street NW, Suite 600, Washington, DC 20005
Countries servedGlobal
Languages1
IntegrationsN/A
Free tierNO
Free trialNO
Contact salesYES

About Solvd

Solvd is an AI engineering services company building production systems, data pipelines, cloud architectures, and agentic software workflows, helping enterprises address scalability, performance, governance, and legacy modernization through custom development engagements rather than a single standardized software application or subscription.

Solvd provides engineering services for organizations moving AI from demonstrations into operational systems. Its offering is organized around Core AI, AI Data and Cloud, and Agentic Software Engineering. Core AI addresses custom systems involving computer vision, natural language processing, and agentic workflows. Data and cloud services support those systems through pipelines, architecture, security, and governance, while agentic engineering combines software expertise with AI-native tooling for delivery and modernization. The supplied material emphasizes production challenges including cost, latency, edge cases, quality controls, and situations where foundation models need supplementation with custom models. Client examples include visual commerce, brain-cell imaging research, retail experience experiments, financial self-service, and payroll tax mapping automation. These examples illustrate previous work rather than capabilities automatically included in every engagement. The payroll example describes a self-validating multi-agent process that flags edge cases for human review, while the research example involves transformer-based analysis of volumetric imaging. Solvd names AWS, Google Cloud, Databricks, and Microsoft as partners and describes work alongside Anthropic and OpenAI. These relationships do not establish prebuilt integrations.

Pros & Cons

Pros
  • Production focus addresses cost, latency, and edge cases beyond initial demonstrations.
  • Combined data, cloud, and governance services support broader AI implementation needs.
  • Custom engineering allows solutions to reflect specific enterprise problems and requirements.
  • Portfolio examples span commerce, financial services, payroll, and scientific research workflows.
Cons
  • Public prices are unavailable, requiring consultation before comparing potential project budgets.
  • Named partnerships do not establish universal prebuilt integrations for every implementation.
  • Case study outcomes do not guarantee equivalent results for other clients.
  • Capabilities depend on agreed scope rather than a standard software package.

Features

Key features

Custom AI Development

Develop custom AI systems for production, using engineering and research capabilities to address computer vision, natural language processing, and agentic workflow requirements within enterprise environments.

Governance and Quality

Apply compliance, safety, and quality layers around AI systems, helping clients address governance requirements while confirming specific controls and responsibilities within their agreed project scope.

Cloud Architecture

Develop cloud architectures for AI workloads, helping organizations coordinate infrastructure and data requirements while defining the platform dependencies and operational arrangements of each proposed implementation.

AI Data Pipelines

Build data pipelines that support AI applications, coordinating information flows with architecture, security, and governance requirements rather than treating data preparation as an isolated task.

Production Scalability

Design for production volume by addressing cost, latency, and operational edge cases, helping organizations move beyond demonstrations toward systems suited to their actual business workloads.

Additional features

Enterprise AI Systems

Develop custom production AI systems across computer vision, natural language processing, and agentic workflows, helping enterprises address specific operational problems rather than selecting functionality from a fixed packaged application catalog.

Data and Infrastructure Engineering

Build data pipelines and cloud architecture around AI applications, coordinating information movement, security, and governance so the supp

Custom Model Development

Create custom models when foundation models plateau on the client’s data, tailoring the technical approach to the problem while confirming training inputs, evaluation methods, and implementation requirements for the engagement.

Edge-Case Engineering

Address edge cases and operational failures during engineering, helping teams prepare systems for scenarios that may not appear in demonstrations but become significant when usage and business dependencies increase substantially.

Cost and Latency Optimization

Optimize cost and latency for production volumes, considering how the proposed system performs under real workloads instead of assuming that successful demonstration performance guarantees commercially viable enterprise deployment at scale.

Pricing

Free trial
Free version
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Countries & Languages

Global
Countries served
1
Interface languages
1
Billing currencies

Interface languages

English

Billing currencies

🇺🇸USD

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