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tkxel joins Anthropic and OpenAI partner networks

2 hours ago
By AI, Created 10:00 UTC, Oct 30, 2026, AGP -

tkxel said it became a Select partner in both Anthropic’s Claude Partner Network and the OpenAI Partner Network in October 2026. The dual memberships give the Reston-based software and AI engineering firm broader access to model support as more customers build task-specific AI systems.

Why it matters: - tkxel now has formal partner access to both Anthropic and OpenAI, two of the most influential AI model providers. - The dual memberships support tkxel’s pitch that businesses do not need to lock into one model for every use case. - The company can now steer client work toward the model that best fits tasks such as code generation, conversation, retrieval and document processing.

What happened: - tkxel joined Anthropic’s Claude Partner Network as a Select Services Partner on October 6, 2026. - tkxel joined the OpenAI Partner Network at the Select tier on October 14, 2026. - The company said the partnerships let it build AI agents and automation for clients on whichever model fits the job.

The details: - Anthropic’s Claude Partner Network is backed by a $100 million investment in partner training, technical support and co-marketing. - Both partnerships give tkxel closer access to technical resources, training and partner support from each provider. - tkxel said it already uses both Claude and OpenAI technology across its own engineering work. - Client results cited by tkxel include Signal, Tenexity, Canvs AI and CCOF. - tkxel said it replaced Signal’s disconnected field operations and sales systems with a single platform. - Claude powers Signal’s lead enrichment and validation layer. - Claude Code cut the build time across engineering, QA and DevOps, and the company said it halved regression cycles while keeping human review in place. - Signal reported 35 percent fewer missed opportunities and 25 percent faster lead-to-close. - Tenexity got an AI-native distribution platform with more than 40 AI workflow applications. - Tenexity reported a 60 percent reduction in manual data entry. - Using the OpenAI API, tkxel said it helped Canvs AI reach 10 times the processing scalability and six times faster insights. - tkxel built a certification search tool for CCOF that made discovery 50 percent faster. - tkxel said its internal AI Unlimited initiative has deployed 600 AI agents across its teams. - The company said the internal program serves as a proving ground for the agent and automation practices it offers clients. - tkxel’s AI work spans AI agents and intelligent workflows, AI-native products and software, and production AI systems covering data integration, evaluation, governance, security and observability. - tkxel serves mid-market businesses across North America in restaurants, security, logistics, fintech and healthcare. - The company employs more than 800 engineers, including over 150 AI professionals, across the United States, Portugal, Saudi Arabia and Pakistan. - tkxel has appeared on the Inc. 5000 list of fast-growing private companies for four consecutive years. - In 2026, tkxel ranked 132nd in the OA500 Global Outsourcing Firm Index, up 70 places from the prior year.

Between the lines: - The move reflects a broader shift in enterprise AI buying, where engineering teams are choosing models based on task rather than standardizing on one vendor. - tkxel is using its own operations as a testbed before selling similar systems to clients, which can strengthen credibility with buyers evaluating automation investments.

What's next: - Businesses evaluating AI agents or workflow automation can book an assessment with tkxel at tkxel.com. - tkxel is likely to continue building client systems across both model ecosystems as demand grows for flexible AI implementations.

The bottom line: - tkxel is positioning itself as a vendor-neutral AI engineering partner with direct access to both major frontier model platforms.

Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.

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