Assistants that cite their source on every answer, escalate with the full context, and are integrated where the work actually lives — CRM, ticketing, ledger. Ungrounded mode off by default. Built for customer-facing or internal use, or both.
We do not ship generic chat boxes. We build conversational assistants whose interaction transcripts pass regulatory compliance audits.
Four standard customer service challenges we address continuously. If one of these scenarios matches your current contact center performance, our collaboration initiates around a query taxonomy, not a high-level presentation deck.
"Support queues are crowded out by the easy questions."
Order status, policy lookups, appointment changes, FAQs. The expensive questions never reach a human, because the queue is full of cheap ones. Deflection lifts the contact-centre cost curve and the agent CSAT at the same time.
"HR, IT and policy questions are eating manager time."
Internal Q&A is the same problem in a different uniform. An assistant grounded in the policy library answers the first ninety percent, and managers get their week back.
"A previous chatbot answered confidently and wrongly."
Most likely it was ungrounded. We replace the model with a retrieval-grounded, citation-by-default architecture — and turn ungrounded mode off at the configuration level.
"Our customers speak more languages than our support team."
We have shipped assistants in 40+ languages including mixed-script and code-switching cases. The model is not the hard part — the data residency and CRM wiring are.
The production-grade conversational stack we deliver to enterprise environments. The language model is a foundational line item; the actual business value resides within the systems integration, data grounding, and escalation workflows.
Seamless consumer, workforce, and partner support across specialised chat widgets, voice portals, and enterprise message routing. Optimised for native web applications, WhatsApp Business, Microsoft Teams, email protocols, Twilio, Genesys, and more.
Bidirectional connections linking virtual assistants directly to your CRM, HRMS, service ticketing tools, and core ledger applications. The system reads secure record layers and writes back transaction histories with full auditable logs.
Granular source citations rendered automatically with every output. Immediate fallback alerts route to human agents whenever system confidence metrics fall below specified thresholds. Fabricated, ungrounded responses are locked down completely at the system layer.
Comprehensive native processing support across forty-plus global languages featuring automated transliteration and conversational code-switching. Complex mixed-script communications are dynamically preserved rather than simplified.
Deep tracking for unexpected intent drift, automated query deflection velocities, root escalation drivers, and granular CSAT correlation metrics. We bypass superficial vanity data to focus strictly on operational metrics that impact budget performance.
Firm domain boundaries, hardcoded regulatory compliance filters, and automated agent handoff parameters. The virtual assistant is programmatically blocked from generating any outputs that contradict your established corporate policy corpus.
“The language model is a commoditized resource. The validation loops, backend enterprise integrations, and human escalation guardrails represent the actual product.”
Talk to an engineerAn active overview of the technological architectures we deploy. Operating seamlessly across voice, web interfaces, applications, and core messaging pipelines—enforcing strict UK and EU data residency wherever your regulatory frameworks demand compliance.
Frontier processing APIs and specialised, fine-tuned open-weight language models—selected purely on empirical evaluation suite results, never superficial demos.
The interactive presentation surfaces and customer touchpoints where your users and corporate workforce interact.
Bidirectional, schema-mapped, and audit-compliant connectors linking conversational tools directly to core enterprise CRM and ticketing pipelines.
Hardened cloud architecture options deploying directly across AWS, Microsoft Azure, and GCP—providing verifiable regional data residency boundaries your compliance teams can easily inspect.
Performance achievements evaluated precisely how contact center operations and customer experience directors measure success—quantified on highly deflectable contact categories, following strict grounding protocols, with transparent CSAT adjustments documented.
Specific engagement target parameters are finalised and committed to in writing during the initial technical Discovery phase.
Our digital automation group ships production platforms through three interconnected technical workstreams. Scalable conversational engines require execution across all three pillars—deeply embedded inside workflow applications, generative at the user layer, and supported by robust backend data pipelines.
The conversational interface operates directly within your native application architecture, core website, or contact center system—not siloed in a disconnected browser tab.
Read more / 02Retrieval-anchored, continuously cited, and tightly governed interactive applications. We replace basic "chat with an LLM" scripts with enterprise software.
Read more / 03Automated intent analytics telemetry, continuous evaluation testing suites, and dedicated adversarial red-team data logs—the structural plumbing that ensures assistant durability.
Read moreWhere assistants land first. Filter by industry to see typical use cases.
Why partner for conversational automation with an engineering organization that explicitly designs and supports production infrastructure.
Every virtual assistant we deploy into production explicitly maps and cites its underlying source record. Ungrounded generation is turned off directly at the system configuration level—not just promised as an abstract concept.
The foundational model is simply a modular component. The core long-term value resides within your CRM networks, ticketing systems, and backend ledger integrations—bidirectional, structured, and entirely audit-aware.
We track real deflection ratios, underlying escalation categories, and net CSAT adjustments. We deliberately ignore superficial metrics like "monthly active users" to focus on numbers that defend your operational expenditures.
Our teams deploy international conversational assistants across forty-plus distinct languages, handling complex code-switching variations and mixed-character scripts instead of basic translated keyword matching.
Every interaction is completely logged: recording the specific generated response, the retrieved text chunk, system confidence levels, and clear escalation paths. The compliance package is an automatic product of the live system, never a retrospective document.
Formally certified across CMMI Level 3, ISO 9001, ISO 27001, and ISO 27701 standards. Delivering localised regional data residency boundaries that align with regulatory frameworks.
Engagements where the deflection target was met, the CSAT delta moved up, and the audit on every conversation was on the page. Filter to widen the view.
CASE 01
US university research initiative
260 years of fragmented historical maps transformed into a georeferenced spatial database for anthropological and land-use analysis. A prominent US university needed to study the historical evolution of Uxeau, France, across multiple centuries of land ownership, taxation, and agricultural activity. The research depended on digitising and harmonising vintage maps dating back to 1759 — each with different scales, formats, and levels of degradation — into a single spatially accurate GIS environment suitable for comparative analysis. 260+ years of historical mapping digitised and layered. Lambert II precision georeferencing using Esri GIS tools. Multi-era land parcel and feature extraction delivered at scale.
30,000+ CT scans annotated at 98.9% segmentation accuracy for AI-driven radiology models. A US-based MedTech AI company developing radiology models for tumour detection and analysis required clinically precise annotation support to accelerate model training and validation. Existing workflows faced rising costs, limited access to qualified medical annotators and growing compliance pressure around handling sensitive patient imaging data.
40%+ faster foreclosure data processing with 50% higher accuracy across multi-county property records. A US-based mortgage data company managing property intelligence across more than 155 million properties and 3,000+ counties required a scalable operational model for foreclosure data collection and processing. Their existing workflows relied heavily on manual back-office operations, creating delays, inconsistencies and rising operational overhead across fragmented government data sources.
The underlying commercial configuration adjusts to your procurement needs; our engineering governance and compliance benchmarks remain unyielding. Whichever deployment option you prioritize, you receive the identical transcript audit trails and system escalation workflows.
An integrated, standing engineering pod that completely manages your conversational roadmap—comprising machine learning developers, UX designers, evaluation analysts, and platform ops.
A specific customer communication channel or targeted intent taxonomy delivered directly to a defined query deflection benchmark.
Expert conversational-AI engineers and software specialists integrated directly into your existing project framework—operating inside your production sprint model while executing to our rigorous code standards.
Conversational automation projects routinely break down in production when they are isolated as mere language model challenges. True stability requires balancing text content formatting, tight enterprise systems integration, and deterministic human escalation guardrails.
Granular query taxonomy mapping, primary source-of-truth system inventory, and explicit deflection target setting. We baseline exactly what successful performance looks like directly on the page.
Conversational flow mapping, safety guardrail enforcement, escalation parameter configuration, and specialised evaluation dataset building. Your absolute compliance posture is locked in on day one.
Agile technical development cycles integrated with an extended shadow-mode operating phase prior to public rollout. The virtual assistant performs silently alongside live human teams before managing traffic autonomously.
Continuous performance tuning loops, automated intent drift tracking, and geographical multi-language expansion. We ensure your deflection metrics remain fully auditable and accurate over time.
“An autonomous virtual assistant built to blindly answer every arbitrary query without strict data grounding is simply a system engineered to provide errors.”
Contact us“We had a chatbot that had been quietly disabled because it answered too confidently. SBL replaced it with one that cites its source on every answer and escalates with the full context. Deflection up 41 percent; CSAT eight points above the human-agent baseline.”Director of Customer Operations UK insurer — Conversational AI — claims-status assistant
Not an ambiguous sales pitch. Provide your top twenty customer interaction intents along with your foundational database profiles, and our engineering architects will deliver a custom deflection-target strategy within five business days.
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